Domination Games on Infinite Graphs
Native Instruments MASCHINE MK3 用户手册说明书
The information in this document is subject to change without notice and does not represent a commitment on the part of Native Instruments GmbH. The software described by this docu-ment is subject to a License Agreement and may not be copied to other media. No part of this publication may be copied, reproduced or otherwise transmitted or recorded, for any purpose, without prior written permission by Native Instruments GmbH, hereinafter referred to as Native Instruments.“Native Instruments”, “NI” and associated logos are (registered) trademarks of Native Instru-ments GmbH.ASIO, VST, HALion and Cubase are registered trademarks of Steinberg Media Technologies GmbH.All other product and company names are trademarks™ or registered® trademarks of their re-spective holders. Use of them does not imply any affiliation with or endorsement by them.Document authored by: David Gover and Nico Sidi.Software version: 2.8 (02/2019)Hardware version: MASCHINE MK3Special thanks to the Beta Test Team, who were invaluable not just in tracking down bugs, but in making this a better product.NATIVE INSTRUMENTS GmbH Schlesische Str. 29-30D-10997 Berlin Germanywww.native-instruments.de NATIVE INSTRUMENTS North America, Inc. 6725 Sunset Boulevard5th FloorLos Angeles, CA 90028USANATIVE INSTRUMENTS K.K.YO Building 3FJingumae 6-7-15, Shibuya-ku, Tokyo 150-0001Japanwww.native-instruments.co.jp NATIVE INSTRUMENTS UK Limited 18 Phipp StreetLondon EC2A 4NUUKNATIVE INSTRUMENTS FRANCE SARL 113 Rue Saint-Maur75011 ParisFrance SHENZHEN NATIVE INSTRUMENTS COMPANY Limited 5F, Shenzhen Zimao Center111 Taizi Road, Nanshan District, Shenzhen, GuangdongChina© NATIVE INSTRUMENTS GmbH, 2019. All rights reserved.Table of Contents1Welcome to MASCHINE (25)1.1MASCHINE Documentation (26)1.2Document Conventions (27)1.3New Features in MASCHINE 2.8 (29)1.4New Features in MASCHINE 2.7.10 (31)1.5New Features in MASCHINE 2.7.8 (31)1.6New Features in MASCHINE 2.7.7 (32)1.7New Features in MASCHINE 2.7.4 (33)1.8New Features in MASCHINE 2.7.3 (36)2Quick Reference (38)2.1Using Your Controller (38)2.1.1Controller Modes and Mode Pinning (38)2.1.2Controlling the Software Views from Your Controller (40)2.2MASCHINE Project Overview (43)2.2.1Sound Content (44)2.2.2Arrangement (45)2.3MASCHINE Hardware Overview (48)2.3.1MASCHINE Hardware Overview (48)2.3.1.1Control Section (50)2.3.1.2Edit Section (53)2.3.1.3Performance Section (54)2.3.1.4Group Section (56)2.3.1.5Transport Section (56)2.3.1.6Pad Section (58)2.3.1.7Rear Panel (63)2.4MASCHINE Software Overview (65)2.4.1Header (66)2.4.2Browser (68)2.4.3Arranger (70)2.4.4Control Area (73)2.4.5Pattern Editor (74)3Basic Concepts (76)3.1Important Names and Concepts (76)3.2Adjusting the MASCHINE User Interface (79)3.2.1Adjusting the Size of the Interface (79)3.2.2Switching between Ideas View and Song View (80)3.2.3Showing/Hiding the Browser (81)3.2.4Showing/Hiding the Control Lane (81)3.3Common Operations (82)3.3.1Using the 4-Directional Push Encoder (82)3.3.2Pinning a Mode on the Controller (83)3.3.3Adjusting Volume, Swing, and Tempo (84)3.3.4Undo/Redo (87)3.3.5List Overlay for Selectors (89)3.3.6Zoom and Scroll Overlays (90)3.3.7Focusing on a Group or a Sound (91)3.3.8Switching Between the Master, Group, and Sound Level (96)3.3.9Navigating Channel Properties, Plug-ins, and Parameter Pages in the Control Area.973.3.9.1Extended Navigate Mode on Your Controller (102)3.3.10Navigating the Software Using the Controller (105)3.3.11Using Two or More Hardware Controllers (106)3.3.12Touch Auto-Write Option (108)3.4Native Kontrol Standard (110)3.5Stand-Alone and Plug-in Mode (111)3.5.1Differences between Stand-Alone and Plug-in Mode (112)3.5.2Switching Instances (113)3.5.3Controlling Various Instances with Different Controllers (114)3.6Host Integration (114)3.6.1Setting up Host Integration (115)3.6.1.1Setting up Ableton Live (macOS) (115)3.6.1.2Setting up Ableton Live (Windows) (116)3.6.1.3Setting up Apple Logic Pro X (116)3.6.2Integration with Ableton Live (117)3.6.3Integration with Apple Logic Pro X (119)3.7Preferences (120)3.7.1Preferences – General Page (121)3.7.2Preferences – Audio Page (126)3.7.3Preferences – MIDI Page (130)3.7.4Preferences – Default Page (133)3.7.5Preferences – Library Page (137)3.7.6Preferences – Plug-ins Page (145)3.7.7Preferences – Hardware Page (150)3.7.8Preferences – Colors Page (154)3.8Integrating MASCHINE into a MIDI Setup (156)3.8.1Connecting External MIDI Equipment (156)3.8.2Sync to External MIDI Clock (157)3.8.3Send MIDI Clock (158)3.9Syncing MASCHINE using Ableton Link (159)3.9.1Connecting to a Network (159)3.9.2Joining and Leaving a Link Session (159)3.10Using a Pedal with the MASCHINE Controller (160)3.11File Management on the MASCHINE Controller (161)4Browser (163)4.1Browser Basics (163)4.1.1The MASCHINE Library (163)4.1.2Browsing the Library vs. Browsing Your Hard Disks (164)4.2Searching and Loading Files from the Library (165)4.2.1Overview of the Library Pane (165)4.2.2Selecting or Loading a Product and Selecting a Bank from the Browser (170)4.2.2.1[MK3] Browsing by Product Category Using the Controller (174)4.2.2.2[MK3] Browsing by Product Vendor Using the Controller (174)4.2.3Selecting a Product Category, a Product, a Bank, and a Sub-Bank (175)4.2.3.1Selecting a Product Category, a Product, a Bank, and a Sub-Bank on theController (179)4.2.4Selecting a File Type (180)4.2.5Choosing Between Factory and User Content (181)4.2.6Selecting Type and Character Tags (182)4.2.7List and Tag Overlays in the Browser (186)4.2.8Performing a Text Search (188)4.2.9Loading a File from the Result List (188)4.3Additional Browsing Tools (193)4.3.1Loading the Selected Files Automatically (193)4.3.2Auditioning Instrument Presets (195)4.3.3Auditioning Samples (196)4.3.4Loading Groups with Patterns (197)4.3.5Loading Groups with Routing (198)4.3.6Displaying File Information (198)4.4Using Favorites in the Browser (199)4.5Editing the Files’ Tags and Properties (203)4.5.1Attribute Editor Basics (203)4.5.2The Bank Page (205)4.5.3The Types and Characters Pages (205)4.5.4The Properties Page (208)4.6Loading and Importing Files from Your File System (209)4.6.1Overview of the FILES Pane (209)4.6.2Using Favorites (211)4.6.3Using the Location Bar (212)4.6.4Navigating to Recent Locations (213)4.6.5Using the Result List (214)4.6.6Importing Files to the MASCHINE Library (217)4.7Locating Missing Samples (219)4.8Using Quick Browse (221)5Managing Sounds, Groups, and Your Project (225)5.1Overview of the Sounds, Groups, and Master (225)5.1.1The Sound, Group, and Master Channels (226)5.1.2Similarities and Differences in Handling Sounds and Groups (227)5.1.3Selecting Multiple Sounds or Groups (228)5.2Managing Sounds (233)5.2.1Loading Sounds (235)5.2.2Pre-listening to Sounds (236)5.2.3Renaming Sound Slots (237)5.2.4Changing the Sound’s Color (237)5.2.5Saving Sounds (239)5.2.6Copying and Pasting Sounds (241)5.2.7Moving Sounds (244)5.2.8Resetting Sound Slots (245)5.3Managing Groups (247)5.3.1Creating Groups (248)5.3.2Loading Groups (249)5.3.3Renaming Groups (251)5.3.4Changing the Group’s Color (251)5.3.5Saving Groups (253)5.3.6Copying and Pasting Groups (255)5.3.7Reordering Groups (258)5.3.8Deleting Groups (259)5.4Exporting MASCHINE Objects and Audio (260)5.4.1Saving a Group with its Samples (261)5.4.2Saving a Project with its Samples (262)5.4.3Exporting Audio (264)5.5Importing Third-Party File Formats (270)5.5.1Loading REX Files into Sound Slots (270)5.5.2Importing MPC Programs to Groups (271)6Playing on the Controller (275)6.1Adjusting the Pads (275)6.1.1The Pad View in the Software (275)6.1.2Choosing a Pad Input Mode (277)6.1.3Adjusting the Base Key (280)6.1.4Using Choke Groups (282)6.1.5Using Link Groups (284)6.2Adjusting the Key, Choke, and Link Parameters for Multiple Sounds (286)6.3Playing Tools (287)6.3.1Mute and Solo (288)6.3.2Choke All Notes (292)6.3.3Groove (293)6.3.4Level, Tempo, Tune, and Groove Shortcuts on Your Controller (295)6.3.5Tap Tempo (299)6.4Performance Features (300)6.4.1Overview of the Perform Features (300)6.4.2Selecting a Scale and Creating Chords (303)6.4.3Scale and Chord Parameters (303)6.4.4Creating Arpeggios and Repeated Notes (316)6.4.5Swing on Note Repeat / Arp Output (321)6.5Using Lock Snapshots (322)6.5.1Creating a Lock Snapshot (322)6.5.2Using Extended Lock (323)6.5.3Updating a Lock Snapshot (323)6.5.4Recalling a Lock Snapshot (324)6.5.5Morphing Between Lock Snapshots (324)6.5.6Deleting a Lock Snapshot (325)6.5.7Triggering Lock Snapshots via MIDI (326)6.6Using the Smart Strip (327)6.6.1Pitch Mode (328)6.6.2Modulation Mode (328)6.6.3Perform Mode (328)6.6.4Notes Mode (329)7Working with Plug-ins (330)7.1Plug-in Overview (330)7.1.1Plug-in Basics (330)7.1.2First Plug-in Slot of Sounds: Choosing the Sound’s Role (334)7.1.3Loading, Removing, and Replacing a Plug-in (335)7.1.3.1Browser Plug-in Slot Selection (341)7.1.4Adjusting the Plug-in Parameters (344)7.1.5Bypassing Plug-in Slots (344)7.1.6Using Side-Chain (346)7.1.7Moving Plug-ins (346)7.1.8Alternative: the Plug-in Strip (348)7.1.9Saving and Recalling Plug-in Presets (348)7.1.9.1Saving Plug-in Presets (349)7.1.9.2Recalling Plug-in Presets (350)7.1.9.3Removing a Default Plug-in Preset (351)7.2The Sampler Plug-in (352)7.2.1Page 1: Voice Settings / Engine (354)7.2.2Page 2: Pitch / Envelope (356)7.2.3Page 3: FX / Filter (359)7.2.4Page 4: Modulation (361)7.2.5Page 5: LFO (363)7.2.6Page 6: Velocity / Modwheel (365)7.3Using Native Instruments and External Plug-ins (367)7.3.1Opening/Closing Plug-in Windows (367)7.3.2Using the VST/AU Plug-in Parameters (370)7.3.3Setting Up Your Own Parameter Pages (371)7.3.4Using VST/AU Plug-in Presets (376)7.3.5Multiple-Output Plug-ins and Multitimbral Plug-ins (378)8Using the Audio Plug-in (380)8.1Loading a Loop into the Audio Plug-in (384)8.2Editing Audio in the Audio Plug-in (385)8.3Using Loop Mode (386)8.4Using Gate Mode (388)9Using the Drumsynths (390)9.1Drumsynths – General Handling (391)9.1.1Engines: Many Different Drums per Drumsynth (391)9.1.2Common Parameter Organization (391)9.1.3Shared Parameters (394)9.1.4Various Velocity Responses (394)9.1.5Pitch Range, Tuning, and MIDI Notes (394)9.2The Kicks (395)9.2.1Kick – Sub (397)9.2.2Kick – Tronic (399)9.2.3Kick – Dusty (402)9.2.4Kick – Grit (403)9.2.5Kick – Rasper (406)9.2.6Kick – Snappy (407)9.2.7Kick – Bold (409)9.2.8Kick – Maple (411)9.2.9Kick – Push (412)9.3The Snares (414)9.3.1Snare – Volt (416)9.3.2Snare – Bit (418)9.3.3Snare – Pow (420)9.3.4Snare – Sharp (421)9.3.5Snare – Airy (423)9.3.6Snare – Vintage (425)9.3.7Snare – Chrome (427)9.3.8Snare – Iron (429)9.3.9Snare – Clap (431)9.3.10Snare – Breaker (433)9.4The Hi-hats (435)9.4.1Hi-hat – Silver (436)9.4.2Hi-hat – Circuit (438)9.4.3Hi-hat – Memory (440)9.4.4Hi-hat – Hybrid (442)9.4.5Creating a Pattern with Closed and Open Hi-hats (444)9.5The Toms (445)9.5.1Tom – Tronic (447)9.5.2Tom – Fractal (449)9.5.3Tom – Floor (453)9.5.4Tom – High (455)9.6The Percussions (456)9.6.1Percussion – Fractal (458)9.6.2Percussion – Kettle (461)9.6.3Percussion – Shaker (463)9.7The Cymbals (467)9.7.1Cymbal – Crash (469)9.7.2Cymbal – Ride (471)10Using the Bass Synth (474)10.1Bass Synth – General Handling (475)10.1.1Parameter Organization (475)10.1.2Bass Synth Parameters (477)11Working with Patterns (479)11.1Pattern Basics (479)11.1.1Pattern Editor Overview (480)11.1.2Navigating the Event Area (486)11.1.3Following the Playback Position in the Pattern (488)11.1.4Jumping to Another Playback Position in the Pattern (489)11.1.5Group View and Keyboard View (491)11.1.6Adjusting the Arrange Grid and the Pattern Length (493)11.1.7Adjusting the Step Grid and the Nudge Grid (497)11.2Recording Patterns in Real Time (501)11.2.1Recording Your Patterns Live (501)11.2.2The Record Prepare Mode (504)11.2.3Using the Metronome (505)11.2.4Recording with Count-in (506)11.2.5Quantizing while Recording (508)11.3Recording Patterns with the Step Sequencer (508)11.3.1Step Mode Basics (508)11.3.2Editing Events in Step Mode (511)11.3.3Recording Modulation in Step Mode (513)11.4Editing Events (514)11.4.1Editing Events with the Mouse: an Overview (514)11.4.2Creating Events/Notes (517)11.4.3Selecting Events/Notes (518)11.4.4Editing Selected Events/Notes (526)11.4.5Deleting Events/Notes (532)11.4.6Cut, Copy, and Paste Events/Notes (535)11.4.7Quantizing Events/Notes (538)11.4.8Quantization While Playing (540)11.4.9Doubling a Pattern (541)11.4.10Adding Variation to Patterns (541)11.5Recording and Editing Modulation (546)11.5.1Which Parameters Are Modulatable? (547)11.5.2Recording Modulation (548)11.5.3Creating and Editing Modulation in the Control Lane (550)11.6Creating MIDI Tracks from Scratch in MASCHINE (555)11.7Managing Patterns (557)11.7.1The Pattern Manager and Pattern Mode (558)11.7.2Selecting Patterns and Pattern Banks (560)11.7.3Creating Patterns (563)11.7.4Deleting Patterns (565)11.7.5Creating and Deleting Pattern Banks (566)11.7.6Naming Patterns (568)11.7.7Changing the Pattern’s Color (570)11.7.8Duplicating, Copying, and Pasting Patterns (571)11.7.9Moving Patterns (574)11.7.10Adjusting Pattern Length in Fine Increments (575)11.8Importing/Exporting Audio and MIDI to/from Patterns (576)11.8.1Exporting Audio from Patterns (576)11.8.2Exporting MIDI from Patterns (577)11.8.3Importing MIDI to Patterns (580)12Audio Routing, Remote Control, and Macro Controls (589)12.1Audio Routing in MASCHINE (590)12.1.1Sending External Audio to Sounds (591)12.1.2Configuring the Main Output of Sounds and Groups (596)12.1.3Setting Up Auxiliary Outputs for Sounds and Groups (601)12.1.4Configuring the Master and Cue Outputs of MASCHINE (605)12.1.5Mono Audio Inputs (610)12.1.5.1Configuring External Inputs for Sounds in Mix View (611)12.2Using MIDI Control and Host Automation (614)12.2.1Triggering Sounds via MIDI Notes (615)12.2.2Triggering Scenes via MIDI (622)12.2.3Controlling Parameters via MIDI and Host Automation (623)12.2.4Selecting VST/AU Plug-in Presets via MIDI Program Change (631)12.2.5Sending MIDI from Sounds (632)12.3Creating Custom Sets of Parameters with the Macro Controls (636)12.3.1Macro Control Overview (637)12.3.2Assigning Macro Controls Using the Software (638)12.3.3Assigning Macro Controls Using the Controller (644)13Controlling Your Mix (646)13.1Mix View Basics (646)13.1.1Switching between Arrange View and Mix View (646)13.1.2Mix View Elements (647)13.2The Mixer (649)13.2.1Displaying Groups vs. Displaying Sounds (650)13.2.2Adjusting the Mixer Layout (652)13.2.3Selecting Channel Strips (653)13.2.4Managing Your Channels in the Mixer (654)13.2.5Adjusting Settings in the Channel Strips (656)13.2.6Using the Cue Bus (660)13.3The Plug-in Chain (662)13.4The Plug-in Strip (663)13.4.1The Plug-in Header (665)13.4.2Panels for Drumsynths and Internal Effects (667)13.4.3Panel for the Sampler (668)13.4.4Custom Panels for Native Instruments Plug-ins (671)13.4.5Undocking a Plug-in Panel (Native Instruments and External Plug-ins Only) (675)13.5Controlling Your Mix from the Controller (677)13.5.1Navigating Your Channels in Mix Mode (678)13.5.2Adjusting the Level and Pan in Mix Mode (679)13.5.3Mute and Solo in Mix Mode (680)13.5.4Plug-in Icons in Mix Mode (680)14Using Effects (681)14.1Applying Effects to a Sound, a Group or the Master (681)14.1.1Adding an Effect (681)14.1.2Other Operations on Effects (690)14.1.3Using the Side-Chain Input (692)14.2Applying Effects to External Audio (695)14.2.1Step 1: Configure MASCHINE Audio Inputs (695)14.2.2Step 2: Set up a Sound to Receive the External Input (698)14.2.3Step 3: Load an Effect to Process an Input (700)14.3Creating a Send Effect (701)14.3.1Step 1: Set Up a Sound or Group as Send Effect (702)14.3.2Step 2: Route Audio to the Send Effect (706)14.3.3 A Few Notes on Send Effects (708)14.4Creating Multi-Effects (709)15Effect Reference (712)15.1Dynamics (713)15.1.1Compressor (713)15.1.2Gate (717)15.1.3Transient Master (721)15.1.4Limiter (723)15.1.5Maximizer (727)15.2Filtering Effects (730)15.2.1EQ (730)15.2.2Filter (733)15.2.3Cabinet (737)15.3Modulation Effects (738)15.3.1Chorus (738)15.3.2Flanger (740)15.3.3FM (742)15.3.4Freq Shifter (743)15.3.5Phaser (745)15.4Spatial and Reverb Effects (747)15.4.1Ice (747)15.4.2Metaverb (749)15.4.3Reflex (750)15.4.4Reverb (Legacy) (752)15.4.5Reverb (754)15.4.5.1Reverb Room (754)15.4.5.2Reverb Hall (757)15.4.5.3Plate Reverb (760)15.5Delays (762)15.5.1Beat Delay (762)15.5.2Grain Delay (765)15.5.3Grain Stretch (767)15.5.4Resochord (769)15.6Distortion Effects (771)15.6.1Distortion (771)15.6.2Lofi (774)15.6.3Saturator (775)15.7Perform FX (779)15.7.1Filter (780)15.7.2Flanger (782)15.7.3Burst Echo (785)15.7.4Reso Echo (787)15.7.5Ring (790)15.7.6Stutter (792)15.7.7Tremolo (795)15.7.8Scratcher (798)16Working with the Arranger (801)16.1Arranger Basics (801)16.1.1Navigating Song View (804)16.1.2Following the Playback Position in Your Project (806)16.1.3Performing with Scenes and Sections using the Pads (807)16.2Using Ideas View (811)16.2.1Scene Overview (811)16.2.2Creating Scenes (813)16.2.3Assigning and Removing Patterns (813)16.2.4Selecting Scenes (817)16.2.5Deleting Scenes (818)16.2.6Creating and Deleting Scene Banks (820)16.2.7Clearing Scenes (820)16.2.8Duplicating Scenes (821)16.2.9Reordering Scenes (822)16.2.10Making Scenes Unique (824)16.2.11Appending Scenes to Arrangement (825)16.2.12Naming Scenes (826)16.2.13Changing the Color of a Scene (827)16.3Using Song View (828)16.3.1Section Management Overview (828)16.3.2Creating Sections (833)16.3.3Assigning a Scene to a Section (834)16.3.4Selecting Sections and Section Banks (835)16.3.5Reorganizing Sections (839)16.3.6Adjusting the Length of a Section (840)16.3.6.1Adjusting the Length of a Section Using the Software (841)16.3.6.2Adjusting the Length of a Section Using the Controller (843)16.3.7Clearing a Pattern in Song View (843)16.3.8Duplicating Sections (844)16.3.8.1Making Sections Unique (845)16.3.9Removing Sections (846)16.3.10Renaming Scenes (848)16.3.11Clearing Sections (849)16.3.12Creating and Deleting Section Banks (850)16.3.13Working with Patterns in Song view (850)16.3.13.1Creating a Pattern in Song View (850)16.3.13.2Selecting a Pattern in Song View (850)16.3.13.3Clearing a Pattern in Song View (851)16.3.13.4Renaming a Pattern in Song View (851)16.3.13.5Coloring a Pattern in Song View (851)16.3.13.6Removing a Pattern in Song View (852)16.3.13.7Duplicating a Pattern in Song View (852)16.3.14Enabling Auto Length (852)16.3.15Looping (853)16.3.15.1Setting the Loop Range in the Software (854)16.4Playing with Sections (855)16.4.1Jumping to another Playback Position in Your Project (855)16.5Triggering Sections or Scenes via MIDI (856)16.6The Arrange Grid (858)16.7Quick Grid (860)17Sampling and Sample Mapping (862)17.1Opening the Sample Editor (862)17.2Recording Audio (863)17.2.1Opening the Record Page (863)17.2.2Selecting the Source and the Recording Mode (865)17.2.3Arming, Starting, and Stopping the Recording (868)17.2.5Using the Footswitch for Recording Audio (871)17.2.6Checking Your Recordings (872)17.2.7Location and Name of Your Recorded Samples (876)17.3Editing a Sample (876)17.3.1Using the Edit Page (877)17.3.2Audio Editing Functions (882)17.4Slicing a Sample (890)17.4.1Opening the Slice Page (891)17.4.2Adjusting the Slicing Settings (893)17.4.3Live Slicing (898)17.4.3.1Live Slicing Using the Controller (898)17.4.3.2Delete All Slices (899)17.4.4Manually Adjusting Your Slices (899)17.4.5Applying the Slicing (906)17.5Mapping Samples to Zones (912)17.5.1Opening the Zone Page (912)17.5.2Zone Page Overview (913)17.5.3Selecting and Managing Zones in the Zone List (915)17.5.4Selecting and Editing Zones in the Map View (920)17.5.5Editing Zones in the Sample View (924)17.5.6Adjusting the Zone Settings (927)17.5.7Adding Samples to the Sample Map (934)18Appendix: Tips for Playing Live (937)18.1Preparations (937)18.1.1Focus on the Hardware (937)18.1.2Customize the Pads of the Hardware (937)18.1.3Check Your CPU Power Before Playing (937)18.1.4Name and Color Your Groups, Patterns, Sounds and Scenes (938)18.1.5Consider Using a Limiter on Your Master (938)18.1.6Hook Up Your Other Gear and Sync It with MIDI Clock (938)18.1.7Improvise (938)18.2Basic Techniques (938)18.2.1Use Mute and Solo (938)18.2.2Use Scene Mode and Tweak the Loop Range (939)18.2.3Create Variations of Your Drum Patterns in the Step Sequencer (939)18.2.4Use Note Repeat (939)18.2.5Set Up Your Own Multi-effect Groups and Automate Them (939)18.3Special Tricks (940)18.3.1Changing Pattern Length for Variation (940)18.3.2Using Loops to Cycle Through Samples (940)18.3.3Using Loops to Cycle Through Samples (940)18.3.4Load Long Audio Files and Play with the Start Point (940)19Troubleshooting (941)19.1Knowledge Base (941)19.2Technical Support (941)19.3Registration Support (942)19.4User Forum (942)20Glossary (943)Index (951)1Welcome to MASCHINEThank you for buying MASCHINE!MASCHINE is a groove production studio that implements the familiar working style of classi-cal groove boxes along with the advantages of a computer based system. MASCHINE is ideal for making music live, as well as in the studio. It’s the hands-on aspect of a dedicated instru-ment, the MASCHINE hardware controller, united with the advanced editing features of the MASCHINE software.Creating beats is often not very intuitive with a computer, but using the MASCHINE hardware controller to do it makes it easy and fun. You can tap in freely with the pads or use Note Re-peat to jam along. Alternatively, build your beats using the step sequencer just as in classic drum machines.Patterns can be intuitively combined and rearranged on the fly to form larger ideas. You can try out several different versions of a song without ever having to stop the music.Since you can integrate it into any sequencer that supports VST, AU, or AAX plug-ins, you can reap the benefits in almost any software setup, or use it as a stand-alone application. You can sample your own material, slice loops and rearrange them easily.However, MASCHINE is a lot more than an ordinary groovebox or sampler: it comes with an inspiring 7-gigabyte library, and a sophisticated, yet easy to use tag-based Browser to give you instant access to the sounds you are looking for.What’s more, MASCHINE provides lots of options for manipulating your sounds via internal ef-fects and other sound-shaping possibilities. You can also control external MIDI hardware and 3rd-party software with the MASCHINE hardware controller, while customizing the functions of the pads, knobs and buttons according to your needs utilizing the included Controller Editor application. We hope you enjoy this fantastic instrument as much as we do. Now let’s get go-ing!—The MASCHINE team at Native Instruments.MASCHINE Documentation1.1MASCHINE DocumentationNative Instruments provide many information sources regarding MASCHINE. The main docu-ments should be read in the following sequence:1.MASCHINE Getting Started: This document provides a practical approach to MASCHINE viaa set of tutorials covering easy and more advanced tasks in order to help you familiarizeyourself with MASCHINE.2.MASCHINE Manual (this document): The MASCHINE Manual provides you with a compre-hensive description of all MASCHINE software and hardware features.Additional documentation sources provide you with details on more specific topics:▪Controller Editor Manual: Besides using your MASCHINE hardware controller together withits dedicated MASCHINE software, you can also use it as a powerful and highly versatileMIDI controller to pilot any other MIDI-capable application or device. This is made possibleby the Controller Editor software, an application that allows you to precisely define all MIDIassignments for your MASCHINE controller. The Controller Editor was installed during theMASCHINE installation procedure. For more information on this, please refer to the Con-troller Editor Manual available as a PDF file via the Help menu of Controller Editor.▪Online Support Videos: You can find a number of support videos on The Official Native In-struments Support Channel under the following URL: https:///NIsupport-EN. We recommend that you follow along with these instructions while the respective ap-plication is running on your computer.Other Online Resources:If you are experiencing problems related to your Native Instruments product that the supplied documentation does not cover, there are several ways of getting help:▪Knowledge Base▪User Forum▪Technical Support▪Registration SupportYou will find more information on these subjects in the chapter Troubleshooting.1.2Document ConventionsThis section introduces you to the signage and text highlighting used in this manual. This man-ual uses particular formatting to point out special facts and to warn you of potential issues. The icons introducing these notes let you see what kind of information is to be expected:This document uses particular formatting to point out special facts and to warn you of poten-tial issues. The icons introducing the following notes let you see what kind of information can be expected:Furthermore, the following formatting is used:▪Text appearing in (drop-down) menus (such as Open…, Save as… etc.) in the software and paths to locations on your hard disk or other storage devices is printed in italics.▪Text appearing elsewhere (labels of buttons, controls, text next to checkboxes etc.) in the software is printed in blue. Whenever you see this formatting applied, you will find the same text appearing somewhere on the screen.▪Text appearing on the displays of the controller is printed in light grey. Whenever you see this formatting applied, you will find the same text on a controller display.▪Text appearing on labels of the hardware controller is printed in orange. Whenever you see this formatting applied, you will find the same text on the controller.▪Important names and concepts are printed in bold.▪References to keys on your computer’s keyboard you’ll find put in square brackets (e.g.,“Press [Shift] + [Enter]”).►Single instructions are introduced by this play button type arrow.→Results of actions are introduced by this smaller arrow.Naming ConventionThroughout the documentation we will refer to MASCHINE controller (or just controller) as the hardware controller and MASCHINE software as the software installed on your computer.The term “effect” will sometimes be abbreviated as “FX” when referring to elements in the MA-SCHINE software and hardware. These terms have the same meaning.Button Combinations and Shortcuts on Your ControllerMost instructions will use the “+” sign to indicate buttons (or buttons and pads) that must be pressed simultaneously, starting with the button indicated first. E.g., an instruction such as:“Press SHIFT + PLAY”means:1.Press and hold SHIFT.2.While holding SHIFT, press PLAY and release it.3.Release SHIFT.Unlabeled Buttons on the ControllerThe buttons and knobs above and below the displays on your MASCHINE controller do not have labels.。
等值图fly图形研究团队
02
等值图技术介绍
等值图定义
等值图是一种可视化技术,用于表示数据点在某个维度上的等值线或等值面。它 通过颜色、线条或符号的变化来表示数值的变化,帮助用户直观地理解数据的分 布和趋势。
等值图通常用于地理信息系统、气象预报、医学影像等领域,以展示空间数据的 连续变化。
非专业用户而言,理解Fly图形的含义和解 读数据的变化趋势也需要一定的学习和训练
。
04
等值图Fly图形研究进展
研究成果展示
01
成果1:等值图算法优化
02
等值图算法是图形渲染中的关键技术,该团队在算法优化 方面取得了重要突破,提高了渲染速度和图像质量。
03
成果2:实时图形渲染技术
04
团队成功研发出实时图形渲染技术,使得图形渲染更为流 畅,减少了延迟,提高了用户体验。
缺点
等值图对于数据的准确性和精度有一定要求,如果数据质量 不高,可能会影响可视化效果;对于大规模数据集,等值图 的计算和渲染可能比较耗时;此外,等值图的可视化效果也 受限于地图投影、比例尺等因素。
03
Fly图形技术介绍
Fly图形定义
总结词
Fly图形是一种基于等值线构建的 二维图形表示方法。
详细描述
Fly图形的优缺点
总结词
Fly图形具有直观、易于理解等优点,但也 存在计算量大、精度要求高等挑战。
详细描述
Fly图形能够清晰地表达数据的空间结构和 变化规律,使得数据可视化结果易于被用户 理解和接受。然而,由于其生成过程涉及大 量的计算和数据预处理,对于大规模和高精 度数据的处理存在一定的难度。此外,对于
介绍电脑游戏功能英语作文
Computer games have become an integral part of modern entertainment,offering a wide range of features that cater to diverse interests and skill levels.Here is an overview of the functionalities that are commonly found in computer games:1.Interactive Storytelling:Many games feature intricate narratives that unfold as the player progresses through the game.Players often make choices that affect the storyline, leading to multiple endings and immersive experiences.2.Realistic Graphics:Advancements in technology have allowed for the creation of stunning visuals in games.Highdefinition textures,realistic lighting,and detailed character models contribute to a more engaging and believable gaming world.3.Multiplayer Capabilities:Online multiplayer features enable players to compete or cooperate with others from around the globe.This includes competitive modes like deathmatches,cooperative missions,and even largescale battles in massively multiplayer online games MMOs.4.Customization Options:Players can often personalize their gaming experience by customizing characters,weapons,and even game settings.This allows for a unique playstyle tailored to individual preferences.5.Achievements and Rewards:Many games incorporate a system of achievements or trophies that players can earn by completing specific tasks or challenges.These rewards can be a source of pride and motivation to explore all aspects of the game.6.Modding Support:Some games offer modding support,allowing players to create and share their own content,such as new levels,characters,or game mechanics.This can greatly extend the life of a game and offer new experiences beyond the original design.7.Virtual Reality VR Integration:With the advent of VR technology,some games offer a fully immersive experience where players can interact with the game world in a threedimensional space,using VR headsets and controllers.8.Esports and Competitive Gaming:Certain games are designed with competitive play in mind,leading to the rise of esports,where professional gamers compete in tournaments with large prize pools and global audiences.9.CrossPlatform Play:Modern games often support crossplatform play,allowing players on different devices,such as PCs,consoles,and mobile devices,to play together seamlessly.cational Content:Some computer games are designed with educational purposes, teaching players about history,science,or problemsolving skills in an engaging and interactive way.11.Accessibility Features:To cater to a wider audience,including those with disabilities, many games include accessibility options such as colorblind modes,adjustable controls, and screen reader compatibility.12.Dynamic Environments:Some games feature dynamic environments that change based on player actions or realworld time,adding an extra layer of realism and immersion.13.Save and Load Systems:Players can save their progress at any point and return to it later,allowing for flexible play sessions and reducing the frustration of losing progress.14.InGame Economies:Many games feature ingame economies where players can earn, trade,or purchase virtual goods,sometimes even with realworld currency.15.Regular Updates and DLC:Developers often release updates and downloadable content DLC to expand the game,fix bugs,and introduce new features,keeping the game fresh and engaging for players.These features not only enhance the gaming experience but also demonstrate the versatility and creativity of the gaming industry,ensuring that there is something for everyone in the world of computer games.。
使命召唤工作室InfinityWard的游戏制作流程
使命召唤工作室InfinityWard的游戏制作流程使命召唤工作室Infinity Ward的游戏制作流程使命召唤系列游戏是世界上最畅销的第一人称射击游戏之一,而Infinity Ward工作室则是该系列游戏的主要开发者之一。
在这个文章中,我们将详细介绍Infinity Ward游戏制作流程的各个阶段。
第一阶段:概念和策划在游戏制作的最初阶段,Infinity Ward团队致力于概念和策划的开发。
这个阶段的目标是确定游戏的整体理念和设计,并制定出一个清晰的游戏开发计划。
团队成员将开会讨论和提出各种创意,并从中选取最合适的概念。
第二阶段:预生产在预生产阶段,Infinity Ward团队将开始制定游戏的详细设计和艺术风格。
程序员、艺术家和设计师等各个职能部门的成员将紧密合作,确保游戏的各个方面都能够协调一致。
此外,这个阶段也包括创建游戏的原型和试验性的游戏机制。
第三阶段:生产一旦预生产阶段完成,Infinity Ward团队将进入到生产阶段。
这是制作游戏的最关键阶段,需要团队成员的密切配合和高效工作。
程序员将开始编码游戏的逻辑和功能,艺术家则负责游戏的美术创作,设计师们将努力创造出有趣和挑战性的游戏关卡。
同时,测试团队也将进行持续的游戏测试,以确保游戏的稳定性和流畅性。
第四阶段:测试与修正一旦游戏的基本功能已经完成,Infinity Ward团队将进行大规模的内部和外部测试。
这些测试旨在寻找并修复游戏中的任何技术或美术问题,同时还会评估游戏的难度平衡和用户体验。
通过反复测试和修正,团队将致力于使游戏更加完美。
第五阶段:发布与支持当游戏通过测试并获得认可后,Infinity Ward团队将准备发布游戏。
在发布之前,他们还将举行一系列的推广活动,以吸引更多的玩家。
一旦发布,团队还将继续支持游戏,修复任何问题并提供新的游戏内容,以保持玩家的兴趣和忠诚度。
总结使命召唤工作室Infinity Ward的游戏制作流程经过了多个阶段的努力和合作。
waters质谱masslynx软件使用说明
Copyright Notice
Micromass UK Limited believes that the information in this publication is accurate. However the information is subject to change without notice and should not be construed as a contractual undertaking by Micromass UK Limited. Despite the care that has been given to the preparation of this publication, Micromass UK Limited accepts no responsibility for any loss or any other matter that may arise from any error or inaccuracy that may inadvertently have been included. Copyright 1993-2002 Micromass Ltd. All Rights Reserved. No part of this publication may be copied without the express written permission of Micromass UK Limited.
Page ii
MassLynx NT Users Guide
Contents
MassLynx NT User’s Guide............................................................................
MaxDEA
Detailed Contents
Chapter 1: Main Features of MaxDEA ..................................................8
1.1 Main Features ............................................................................................... 8 1.2 Models in MaxDEA...................................................................................... 9 1.3 What’s NEW ............................................................................................... 12 1.4 Compare MaxDEA Editions ..................................................................... 17
3.1 Import Data ................................................................................................ 19 3.2 Define Data ................................................................................................. 24 3.3 Set and Run Model..................................................................................... 25 3.4 Export Results ............................................................................................ 77
我想玩一个游戏作文英语
Playing games can be a delightful and engaging activity,offering a variety of benefits such as entertainment,relaxation,and even cognitive development.Heres an essay on the topic of playing a game in English:The Joy of Gaming:An English PerspectiveIn the digital age,the world of gaming has expanded beyond the confines of traditional board games and sports.Video games,in particular,have become a significant part of many peoples lives,offering an immersive experience that can be both entertaining and educational.The Appeal of Video GamesVideo games come in various genres,catering to different tastes and preferences.From actionpacked adventures to strategic simulations,the diversity of games ensures that there is something for everyone.The interactive nature of these games allows players to become part of the story,making decisions that influence the outcome.This level of engagement is one of the reasons why video games are so popular.Cognitive BenefitsPlaying games,especially those that require strategic thinking and problemsolving,can have cognitive benefits.They can improve memory,enhance spatial awareness,and even boost creativity.For example,puzzle games challenge players to think logically and creatively to solve complex problems,which can be a great mental workout.Social InteractionGaming is not just a solitary activity.Many games are designed to be played with others, either in the same room or online.This social aspect of gaming can help build teamwork skills and foster communication among players.Multiplayer games,in particular,can create a sense of community and camaraderie among those who share a common interest in the game.The Role of CompetitionCompetition is a key element in many games,whether its racing to the finish line in a racing game or battling it out in a fighting game.This competitive spirit can bemotivating and can push players to improve their skills.However,its important to remember that games should be enjoyed in a spirit of fun and sportsmanship.Balancing Gaming with Other ActivitiesWhile gaming can be a rewarding and enjoyable pastime,its crucial to maintain a balance with other aspects of life.Spending excessive time gaming can lead to neglecting responsibilities such as schoolwork,physical exercise,and social interactions.Its important to set limits and ensure that gaming is just one part of a wellrounded lifestyle.ConclusionIn conclusion,playing games,whether they are video games or traditional board games, can be a fun and enriching experience.They offer a chance to relax,engage with others, and even develop new skills.As long as they are enjoyed in moderation and as part of a balanced routine,games can be a positive addition to ones life.This essay provides a comprehensive look at the world of gaming,discussing its appeal, benefits,and the importance of maintaining a healthy balance in ones gaming habits.。
Adobe Acrobat SDK 开发者指南说明书
This guide is governed by the Adobe Acrobat SDK License Agreement and may be used or copied only in accordance with the terms of this agreement. Except as permitted by any such agreement, no part of this guide may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical, recording, or otherwise, without the prior written permission of Adobe. Please note that the content in this guide is protected under copyright law.
安徽师范大学学报(自然科学版)第45卷第1-6期(总第192-197期)2022年总目次
安徽师范大学学报(自然科学版)第45卷第1-6期(总第192-197期)2022年总目次古典诗词中的运动相对性……………………………………………………………………………丁光涛(1.1)主题内容智能聚合技术的研究和应用…………………………………………邵德奇,关培培,石聪(2.103)旋转式超导磁通泵电磁特性分析………………………………………………方进,陈海峰,陈洁(3.205)网络舆情对公共政策影响的研究…………………………………………………邵德奇,冯超,王丽萍(5.409)铅冷快堆中铁基结构材料液态金属腐蚀的第一性原理研究………………刘长松,张静丹,张艳革,等(6.511)基于高阶矩冲击机器学习Multi-LSTM模型的中国碳价预测…………………云坡,陈江华,唐文之(1.6)关于近拟常曲率空间中2-调和子流形…………………………………………叶闻,宋卫东,耿杰(1.13)Q-m-clean环及其推广……………………………………………………………………李莹,殷晓斌(1.18)图的全-Domination染色……………………………………………………………………………王彩云(1.23)基于数值积分的最佳平方逼近样条函数………………………………………………钱江,刘雯星(2.107)近拟常曲率空间中某类紧致超曲面……………………………………………………钟家伟,宋卫东(2.117)一类具有时滞的捕食—食饵模型的Hopf分支…………………………………………赵童,袁海龙(2.121)基于深度神经网络的WiFi室内定位算法研究……………………………李志祥,丁绪星,陈兴盛,等(2.131)一元五次B样条拟插值研究……………………………………………………………钱江,王永杰(3.212)隐变量对EM算法的影响………………………………………………………刘芝秀,吕凤姣,李运通(3.221)变系数Pavlov方程的李对称分析、精确解和守恒律…………………………胡玉茹,张峰,辛祥鹏(4.307)几类操作图的全控制染色………………………………………………………王彩云,李敏慧,张淑敏(4.318)具有惯性项的粘性Cahn-Hilliard方程的指数吸引子……………………张晓雨,姜金平,王小霞,等(4.325)同时反演时间分数阶方程的灌注系数和初始温度………………………………………………黄洁(5.415)一种充分下降的修正共轭梯度法………………………………………………胡倩蕊,周光辉,曹尹平(5.424)基于INF-Deffuant模型的网络用户观点演化分析…………………………刘玉文,翟菊叶,潘玮,等(5.433)具有收获和避难所效应的捕食—食饵系统Hopf分支分析…………………张道祥,李梦婷,闫晴,等(6.522)Medium J 12-clean环和Medium 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OF ANHUI NORMAL UNIVERSITY (Natural Science)Vol.45No.1-6(Sum No.192-197)2022CONTENTSMotion Relativity in Chinese Classic Poetry………………………………………………DING Guang-tao(1.1)Research and Application of Intelligent Aggregation Technology for Subject Content…………………………………………………………………………………………………SHAO De-qi,GUAN Pei-pei,SHI Cong(2.103)Analysis of Electromagnetic Characteristics of Rotating Superconducting Flux Pump…………………………………………………………………………………………………F ANG Jin,CHEN Hai-feng,CHEN Jie(3.205)Research on the Impact of Online Public Opinion on Public Policy……………………………………………………………………………………………………………………SHAO De-qi,FENG Chao,WANG Li-ping(5.409)First-Principles Study on Liquid Metal Corrosion of Iron-Based Structure Materials in Lead-Cooling Fast Reactor ………………………………………………LIU Chang-song,ZHANG Jing-dan,ZHANG Yang-ge,et,al.(6.511)China's Carbon Price Prediction Based on Machine Learning Multi-LSTM Model from the Perspective of High-Order Moment Impact………………………………………YUN Po,CHEN Jiang-hua,TANG Wen-zhi(1.6)On the2-Harmonic Submaniflods of Nearly Quasi Constant Curvature Space………………………………………………………………………………………………………………YE Wen,SONG Weidong,Geng Jie(1.13)Q-m-clean Rings and its Generalization………………………………………………LI Ying,YIN Xiao-bin(1.18)Total-Domination Coloring of Graphs………………………………………………………WANG Cai-yun(1.23)The Best Square Approximating Spline Functions Based upon Numerical Inteyration………………………………………………………………………………………………………………QAIN Jiang,LIU Wen-xing(2.107)On Compact Hypersurfaces in Nearly Quasi Constant Curvature Space…ZHONG Jia-wei,SONG Wei-dong(2.117)Bifurcation Analysis of a Predator-Prey System with Time Delay…………ZHAO Tong,YUAN Hai-long(2.121)Indoor Positioning Algorithm for WiFi Based on Deep Neural Network…………………………………………………………………………………………………LI Zhi-xiang,DING Xu-xing,CHEN Xing-sheng,et al.(2.131)On Univariate Quintic B Spline Quasi-Interpolation………………………QIAN Jiang,WANG Yong-jie(3.212)Influence of Hidden Variables on EM Algorithm…………………LIU Zhi-xiu,LV Feng-jiao,LI Yun-tong(3.221)Lie symmetry Analysis,Exact Solutions and Conservation Laws to the Variable Coefficients Pavlov Equation……………………………………………………………………HU Yu-ru,ZHANG Feng,XIN Xiang-peng(4.307)《安徽师范大学学报(自然科学版)》2022年(第45卷)总目次45卷第6期Total Dominator Chromatic Number with Several Types of Operations Graphs…………………………………………………………………………………………………WANG Cai-yun,LI Min-hui,ZHANG Shu-min(4.318)Exponential Attractors for Viscous Cahn-Hilliard Equation with Inertial Term………………………………………………………………………………………ZHANG Xiao-yu,JIANG Jin-ping,WANG Xiao-xia,et al.(4.325)Simultaneous Inversion of Perfusion Coefficient and Initial Temperature of Time Fractional Equation…………………………………………………………………………………………………………………HUANG Jie(5.415)A Modified Conjugate Gradient Method With Sufficient Descent………………………………………………………………………………………………………………HU Qian-rui,ZHOU Guang-hui,CAO Yin-ping(5.424)Evolutional Analysis of Network Users’Opinion Based on an INF-Deffuant Model…………………………………………………………………………………………………LIU Yu-wen,ZHAI Ju-ye,P AN Wei,et al.(5.433)Hopf Bifurcation Analysis in a Predator-Prey Model with Predator Harvesting and Prey Refuge……………………………………………………………………ZHANG Dao-xiang,LI Meng-ting,YAN Qing,et al.(6.522)Medium J 12-clean rings and Medium J12-∗-clean rings…………………………TAO Dan-dan,YIN Xiao-bin(6.534)Research on Intelligent Image Identification Technology of Power Equipment Inspection Defects………………………………………………………………………………LYU Qiang,WANG Wei,MA Guo-qiang,et al.(6.545)Theory and Experimental Verification of Three-Mode Coupled Mode Based on Lagrange Equation……………………………………………………………Z HANG Ya-bo,DING Zhong-zheng,PENG Xue-cheng,et al.(3.227)Fourier Transforms in Signals and Systems from the Perspective of Sampling……………………………………………………………………………………………………………WANG Lin,HU Yao,WANG Shi-yuan(4.332)Study on the Influence of Mineral Admixtures on the Durability of Lightweight Aggregate Concrete………………………………………………………………………………………………………………TANG Peng(2.139)Research Progress in the Detection Methods of Polycyclic Aromatic Hydrocarbons in Foods………………………………………………………………………………QIN Zheng-bo,WANG Qiao-lin,WANG Lin,et al.(1.29)Identification and Optimization of Ecological Network in Ma'anshan City……………………………………………………………………………………………ZHOU Zhen-hong,WANG Hui-hui,ZHU Qing-shan,et al.(1.35)Pollution Characteristics and Potential Source Areas of Gaseous Pollutants During the Heating Period in Northern Core Cities from2014to2020…………………………MA Kang,LIN Yue-sheng,F ANG Feng-man(3.237)Research on the Measurement and Improvement of Ecological Efficiency Level in Hefei Metropolitan Area from 2015—2020………………………………………………………………LIU Yu-wan,WU Xu-zhong(3.244)Heavy Metal Pollution and Risk Assessment of Soil around Polymetallic Mining Area……………………………………………………………………………………………CAO Yuan-dan,CAO Yu-hong,YU Dai-liang(4.338)Dynamic Simulation of Land Use and Landscape Ecological Risk Assessment in Lu'an City……………………………………………………………………………ZHOU Zhen-hong,LIU Dong-yi,WANG Shi-qi,et al.(5.443)VVI安徽师范大学学报(自然科学版)2022年The Effects of Melatonin on Seed Germination,Seedling Growth and Physiology of Miscanthus Sacchariflorus ………………………………………………………LIANG Yu-peng,ZHANG Jie,LIANG Xiao-ning,et al.(6.554)Floristic Difference of Emmenopterys henryi munity in Different Regions………………………………………………………………………………………ZANG Min,CHEN Xiao-yu,HUANG Wen-zi,et al.(1.42)Analysis of Amphibian and Reptile Biodiversity and Floristic Characteristics in Qingyang County and Shitai County,Anhui,China……………………WANG Bin,YANG Liu-yang,WANG Ming-sheng,et al.(2.144)Spatiotemporal Change Characteristics and Influencing Factors of Rural Residential Land Use in the Yangtze Riv-er Delta…………………………………………………ZHONG Jun-yu,YANG Xing-zhu,ZHU Yue(1.49)Research on Spatial Characteristic of Railway Passenger Station Accessibility Based on Cost Distance…………——A Case of Gansu Province……………………WANG Yan-bin,HE Ruidong,WANG Ya-ni,et al.(1.58)Spatial Distribution Characteristics and Influencing Factors of Cafes in Small and Medium-Sized Cities…………——A Case Study of Wuhu City………………………………………YIN Shou-bing,ZHANG Jian(1.64)Study on the Spatial Mismatch Between the A-Level Tourist Attractions and the Quality of Inbound Tourism in Yunnan Province…………………………………………WU Jia-yi,CHEN Ya-pin,JIAO Min,et al.(1.71)The Influence of Social Presence on the Value Co-Creation Behavior of Online Tourism Community……………………………………………………………………………………………………………………ZOU Yan(1.78)Distribution Characteristics and Influencing Factors of Soil Black Carbon in Lushan Mountain…………………………………………………………………………CUI Meng-fan,WANG Qing,FENG Wei-hao,et al.(2.154)Study on the Measurement of the Characteristics of Land Use Transformation in Mountainous Villages ——A Case Study of Shiyao Village in Tongcheng City……………………………………………………………………………………………………………WANG Yong-zheng,ZHAN An-ting,YU Hao-ran,et al.(2.160)The Construction of Evaluation System of Pre-Service Geography Teachers’Key Competencies………………………………………………………………………………MIAO Yu-qing,ZHANG Ru-nan,LIANG Ning(2.170)The Impacts of High-Speed Transportation on Regional Accessibility in Lu'an——From the Perspective of Equity and Efficiency……………………………………………ZHANG Lu-lu,WU Wei,WANG Jin,et al.(3.251)Study on the Change of Spatial Form of Small and Medium-Sized Cities in Wanjiang Basin——Take Guichi Dis-trict of Chichou City as an Example……………………………………LIU Yang,CHEN Bao-ping(3.260)Characteristics of the Spatial Pattern Evolution and Its Influencing Factors of Production-Living-Ecological Space in Tourist Destinations——Take the Eco-Tourism Cooperation Zone of Zhejiang-Anhui-Fujian-Jiangxi as an Example……………………………………………GUO Yu-yun,YANG Xing-zhu,ZHU Yue,et al.(3.267)Spatial Distribution Characteristics and Influencing Factors of Homestays in Xuancheng…………………………………………………………………………………………………………WANG Xi,YANG Xiao-zhong(3.278)VII 45卷第6期《安徽师范大学学报(自然科学版)》2022年(第45卷)总目次Effects of Urbanization on Vegetation Change in Anhui Province Based on NDVI…………………………………………………………………………………HUANG Zuo-hui,LIANG Dong-dong,GUI Xiang,et al.(4.345)The Thermal Contribution of Urbanization Change Trajectory to Surface Temperature in Hefei City during33 Years………………………………………………ZHOU Hua,WU Qing-shuang,LI Qiang,et al.(4.356)Research on the Optimization of Red Tourism Experience Degree in Yan'an from the Perspective of Regional Syn-ergy………………………………………………………………………………CUI Yan,LIU Dong(4.365)Research on Tourists蒺Perceived Value of Cloud Tourism of the Palace Museum…………………………………………………………………………………………………………CHENG Ru-xia,HUANG An-min(4.373)Spatial Distribution Characteristics and Influencing Factors of Soil Nutrient in the Hilly Polder Terrain Area along the River in the Lower Reaches of the Yangtze River…………CAO Yu,F ANG Li,YU Jian,et al.(5.453)Temporal and Spatial Variation Characteristics of Vegetation Cover and Climate Response in the Yangtze River Delta………………………………………………………………WANG Yi-ling,LIANG Dong-dong(5.462)Spatial Differentiation of Urban Agglomeration Development in China……………DAI He-zhi,JIANG-Ge(5.469)The Spatial-Temporal Differentiation haracteristics of Urban Resilience and Influencing Factors in China……………………………………………………………………………SHAN Xin-meng,HE Min,LI Rui,et al.(5.476)The Impact of Monetization Resettlement on House Prices——Based on the Empirical Evidence of Prefecture-Level Cities in Anhui Province………………………………HOU Xi-wu,WANG Man-yin,WU Xin(6.561)Identification and Response of Driving Factors of Rural Tourism in Chizhou City Based on PCA-PLS Analysis ………………………………………………………JI Kai-ting,WANG Wen-qin,LI Qiong,et,al.(6.567)Knowledge Mapping Analysis of Cultural Tourism Reserach in China………………………………………………………………………………………………WU Cheng-cheng,ZHOU Guo-zhong,WANG Yun-yun(6.575)Experimental Research on the Influence of Functional Training on the Sports Quality of University Dragon Boat Athletes…………………………………………………LIU Xiao,WANG Jie-chun,LV Guang-ming(1.85)Analysis of the Implementation Effect of National Students'Physical Health Standard(Revised in2014)in High-er V ocational Colleges of Anhui Province……………………………………SHEN Cai-die,LIU Ying(1.91)Characterization of Martial Arts Field Diversity of Martial Arts Types——Textual Examination Based on the Vid-eo Ethnography The Hidden Martial Arts……………………………………WANG Jie,HUA Jia-tao(1.97)An Empirical Study on the Teaching of Upper Limb Strength Training for Beginners in Crawl Swimming……………………………………………………………………………WU Jia-fang,ZHANG Nan,ZHOU Kun(2.177)Analysis on the Action Mechanism of Shoulder Joint in Tennis Serve Technique…………SUN Yong-mei(2.183)Meta鄄Analysis about the Effects of Plyometric Training on Change of Direction Speed………………………………………………………………………………LI Xue-liang,LI Chun-man,F ANG Zuo-ming,et al.(3.288)VIII安徽师范大学学报(自然科学版)2022年South Korean Sports Tourism Development Experience and Inspiration…………………………………………………………………………………………………WANG Ning,WANG Lu-juan,SUN Wan-ting,et al.(3.299)Research on the Implementation Path of Improving the Basic Physical Fitness Training Level of Chinese Elite Swimmers——Take Preparation for Tokyo Olympic Games as an Example…………………………………………………………………………………………DONG-Qi,WANG Jie-chun,CUI Deng-rong,et al.(4.380)Value,Problems and Countermeasures:Development of Sports in Rural Revitalization……………………………………………………………………………………………………ZHANG Chang-nian,AO Wen-jie(4.387)Multiple Regression Analysis of the Influence of College Students'Sports Participation on their Physical Health …………………………………………………………………………………………HUANG Zheng-feng(4.395)Study on the Surface Electromyographic Force Characteristics of Female Gymnast He Licheng in the Sports Event of Balance Beam……………………WANG Zheng,YUE Jian-jun,XU Zhuang-zhuang,et al.(4.402)The Reality Examination about Development of Rural Sports Leisure Industry…………………………………………………………………………………………………………………SHAN Fu-bin,CHENG Jin-yang(5.485)Multi-Dimensional Interpretation of Accelerating China’s Sports Power Construction during the14th Five-Year Plan Period…………………………………………………………………………SHEN Wei,LIU Li(5.492)On Changes and Invariance in the Development of Technical Style of Chinese Badminton Team………………………………………………………………………………………………………………………YANG Xu(5.499)On a New Discipline:the Construction of Sports Learning Sciences……………………………………………………………………………………………………………………………JIANG Ming,ZHANG Zhen-hua(5.506)Analysis on the Current Situation of Differentiated Development of Tennis Physical Fitness Training………………………………………………………………………………………………………………LI Zhu-qing(6.584)Research on the Current Situation and Improvement Path of"Three Dimensions"of Physical Education Core Competence of High School Students in Anhui Province………………………GE Bei,WU Jing-xin(6.589)Research on the Influence of Science and Engineering Talents on Total Factor Productivity of Enterprises ——Evidence from College Enrollment Expansion………………ZHOU Duan-ming,HOU Xiao-ru(2.189)The Application of Big Data for Readers in Reading Promotion of University Libraries——Based on Data of NLSP from Nanjing University Library……………………………………………ZHANG Kan-ning(2.197)Research on the Competitive Strategy Choice of5G Service of A Mobile Company…………………………………………………………………………………………………………YANG Yang,ZHANG Ting-long(6.596)The Relationship Between Work-family Balance and Social Support Among Young Professional Women:Based on potential Profile Analysis…………………………………………WANG Jing,F ANG Shuang-hu(6.607)。
图的独立的罗马2-控制
摘要摘要在任意图G =(V,E )中,我们定义函数f :V →{0,1,2}是一个罗马2-控制函数,若f 满足:对于每个赋值为0的点,要么至少与一个赋值为2的点相邻,要么至少与两个赋值为1的点相邻.令V i ={v ∈V :f (v )=i },i =0,1,2.若一个罗马2-控制函数f 满足V 1∪V 2是一独立集,则称f 是独立的罗马2-控制函数.独立的罗马2-控制函数的权重ω(f )=∑︀v ∈V f (v ),其中最小的权重称为图G 的独立的罗马2-控制数,记作i {R 2}(G ).∙在第一章,我们介绍了控制集的研究背景以及一些术语和记号.∙在第二章,给出了一般图的独立的罗马2-控制函数的一些性质,并且给出了P n ,C n ,P 2 C n ,C 3 C n 的独立的罗马2-控制数.∙在第三章,我们刻画了i {R 2}(G )=γ(G )+1的树,单圈图,块图以及仙人掌图.另外,也刻画了i {R 2}(G )=γ(G )+2的树.∙在第四章,给出了一个计算i {R 2}(T )的线性时间算法.关键词:罗马2-控制数;独立的罗马2-控制数;树;单圈图;块图;仙人掌图.iAbstractAbstractFor a graph G =(V,E ),a Roman {2}-dominating function f :V →{0,1,2}has the property that for every vertex v ∈V with f (v )=0,either v is adjacent to at least one vertex u for which f (u )=2,or at least two vertices u 1and u 2for which f (u 1)=f (u 2)= 1.Let V i ={v ∈V |f (v )=i }for i =0,1,2.A Roman {2}-dominating function f is called independent if V 1∪V 2is an independent set.The weight of an independent Roman {2}-dominating function f is the value ω(f )=∑︀v ∈V f (v ),and the independent Roman {2}-domination number i {R 2}(G )is the minimum weight of an independent Roman {2}-dominating function on G .∙In the first chapter,we first introduce the research background of domi-nation.Then we give some main notions and graph theoretical terminologies.∙In the second chapter,we give some properties of independent Roman {2}-dominating function in general graphs.Moreover,we give the exact value of the independent Roman {2}-domination number of P n ,C n ,P 2 C n ,C 3 C n .∙In Chapter 3,we characterize all trees,unicyclic graphs,block graphs and cactus graphs with i {R 2}(T )=γ(T )+1.Moreover,we also characterize all trees T for which i {R 2}(T )=γ(T )+2.∙In Chapter 4,we present a linear time algorithm to compute the value of i {R 2}(T )for any tree T .Key Words:Roman {2}-domination number;Independent Roman {2}-domi-nation number;Tree;Unicyclic graph;Block graph;Cactus graph.目录第一章引言 (1)S1.1问题背景 (1)S1.2术语和记号 (2)第二章独立的罗马2-控制函数的性质 (4)S2.1引言 (4)S2.2预备知识 (4)S2.3独立的罗马2-控制函数的性质 (5)第三章具有特定独立的罗马2-控制数的图 (10)S3.1引言 (10)S3.2预备知识 (10)S3.3具有特定独立的罗马2-控制数的树 (12)S3.4具有特定独立的罗马2-控制数的单圈图,块图以及仙人掌图 (22)第四章对任意树T,计算i{R2}(T)的线性时间算法 (36)参考文献 (39)致谢 (42)第一章引言S1.1问题背景图论是离散数学的一个分支,它起源于一个著名的数学问题:哥尼斯堡七桥问题,实质上就是我们现在所说的“一笔画”问题.瑞典数学家欧拉将这个问题转化为由点和线组成的图形的问题,最终解决了这个问题,开创了图论.从19世纪中叶开始,图论迎来研究和发展的热潮,这一时期图论问题大量涌出,诸如关于地图染色的四色问题,由“周游世界游戏”发展起来的哈密顿问题等.另外,图论也广泛渗透在计算机科学领域中,在计算机科学领域中存在着各种各样的图论算法.图的控制数理论作为图论的一个重要的研究领域,在相关科学,如计算机科学,通信网络,编码理论,监视系统和社会网络等领域中有着重要的作用.在19世纪50年代,欧洲的国际象棋爱好者们提出了这样一个问题:如何在棋盘上放置最少数量的皇后,使得所有方格要么被皇后攻击,要么被皇后占据.控制棋盘上方格的问题可以更一般地表述为控制图中顶点的问题.这一问题引起了学者们的兴趣,图的控制数理论得以发展.1962年,Berge在文献[1]中给出了我们现在所熟知的“控制数”的概念.同年,由Ore正式定义控制集,控制数以及术语“dominating set”和“domination number”.1977年,在文献[2]中,Cockayne和Hedetniemi首次使用γ(G)这一记号,并用于表示图G的最小控制数.接着1979年,Garey和Johnson在文献[9]中证明了判定一般图的最小控制集问题是NP-困难的.对于控制集问题,我们还可以阅读文献[12].基于不同的实际背景,学者们提出了不同形式的控制函数去解决不同的实际问题.例如,在文献[22]中,Stewart提到了“罗马控制”的概念.Cockayne et al.(2004)在文献[3]中,给出了罗马控制函数的一些性质以及罗马控制数的上下界.另外,文章还给出了P n,C n,完全n-部图K m以及P2 C n的罗马控制1,···,m n数.最后,作者刻画了γR(T)=γ(T)+1以及γR(T)=γ(T)+2的树.关于罗马控制问题的研究,更多地可以参阅文献[4,10,17].Chellali et al.(2016)在文献[5]给出了罗马控制函数的一个新的变形—罗马2-控制函数.在这篇文章中,他们首先证明了罗马2-控制数可作为其他控制函数(包括控制数,罗马控制数,2-控制数以及弱罗马控制数)的界,并利用这些结果给出了关于这5个控制参数之间的不等式关系:γ(G)≤γr(G)≤γ{R2}(G)≤γr2(G)≤γR(G)≤2γ(G).特别地,作者还证明了任意树以及没有偶圈的仙人掌图均满足γ{R2}(G)=γr2(G).另外,作者还给出了P n,C n的罗马2-控制数,而这一结果将用于后面i{R2}(P n)以及i{R2}(C n)的确定.在文章的最后,他们证明了即使是二部图,关于罗马2-控制数的判定问题是NP-完全的.而关于罗马2-控制函数的研究,我们还可以参阅文献[11].在这篇文章中, Henning et al.将罗马2-控制称作“意大利控制”,并用γI表示意大利控制数.文中,他们的主要工作是刻画γI(T)=γ(T)+1以及γI(T)=2γ(T)的树,这也为我们研究独立的罗马2-控制函数提供了研究方向与想法.在文献[21]中,Rahmouni和Chellali在罗马2-控制函数的基础上提出了“独立的罗马2-控制函数”的定义.在这篇文章中,他们证明了即使是二部图,关于独立的罗马2-控制数的判定问题是NP-完全的.接着他们还给出了i r2(G)−i{R2}(G)以及i R(G)−i{R2}(G)的上界.在这篇文章的最后,他们提出了一些未解决的问题.受这篇文章的启发,本文将针对独立的罗马2-控制问题展开进一步研究.S1.2术语和记号一般我们依旧采用文献[13]里的符号与术语.本文所涉及到的图都是有限的,无向的简单图.用G=(V,E)表示一个图,其中V=V(G)为图G的顶点集,E=E(G)为图G的边集.对任意一点v∈V(G),v的开邻集N(v)为图G中所有与v相邻的点构成的集合,即N(v)={u:uv∈E(G)}.点v的闭邻集为N[v]=N(v)∪{v}.在图G中,点v的度为d(v)=d G(v)=|N(v)|.度为1的点称为叶子点.叶子点的邻点称为支撑点,与叶子点关联的边称为悬挂边.令v ∈S ⊆V ,若存在一点w ∈N (v )∩(V −S )满足N (w )∩S ={v },我们称w 是v 的S -私邻点.若S ⊆V 中任意两点在G 中均不相邻,则称S 为G 的一个独立集.一个子集S ⊆V ,若满足V −S 中的每一点都至少与S 中的p 个顶点相邻,则称S 为图G 的一个p -控制集.G 的最小p -控制集的基数称为G 的p -控制数,记作γp (G ).注意到1-控制数γ1(G )也就是通常所说的控制数γ(G ).图G 中所有的最小p -控制集都可称为γp -集.函数f :V →{0,1,2}是一个罗马控制函数,若f 满足:对于每个赋值为0的点,至少与一个赋值为2的点相邻.罗马控制函数的权重为ω(f )=∑︀v ∈V f (v ).值得一提的是,现在已经有许多文章对罗马控制函数有了详尽的研究,可以参考文献[3,10,5].另外,在文献[20,6]中介绍了罗马控制函数的一些变形.一个函数f :V →{0,1,2}是一个罗马2-控制函数,若f 满足:对于每个赋值为0的点,要么至少与一个赋值为2的点相邻,要么至少与两个赋值为1的点相邻.我们用γ{R 2}(G )表示图G 的罗马2-控制数.令V i ={v ∈V :f (v )=i },i =0,1,2.若一个罗马2-控制函数f 满足V 1∪V 2是一独立集,则称f 是独立的罗马2-控制函数(IR2DF).独立的罗马2-控制函数的权重为ω(f )=∑︀v ∈V f (v ),其中最小的权重称为图G 的独立的罗马2-控制数,记作i {R 2}(G ).若函数f 是图G 的独立的罗马2-控制函数且ω(f )=i {R 2}(G ),那么称f 是G 的i {R 2}-函数.注意到函数f 与V 的一个划分(V 0,V 1,V 2)是1−1对应的,所以独立的罗马2-控制函数可记作f =(V 0,V 1,V 2).第二章独立的罗马2-控制函数的性质S2.1引言文献[16]给出了一般图满足γ2(G)=γ(G)的必要条件,受此启发,我们给出了满足i{R2}(G)=γ(G)的必要条件,以及满足i{R2}(G)≥γ(G)+1的充分条件.特别地,对任意非平凡的树T,有i{R2}(T)≥γ(T)+1.该结论主要用于第三章树的刻画.Chellali et al.(2016)在文献[5]中给出了P n,C n的罗马2-控制数,而这一结果将用于后面i{R2}(P n)以及i{R2}(C n)的确定.文献[19]中,Nandi等人给出了P m C n的控制数,其中m=2,3,4,n≥3.Shaheen在文献[24]给出了C m C n的2-控制数,其中m=3,4,5,6,7.在2017年,Shaheen等人在文献[23]中给出了P m P n的2-控制数,其中m=1,2,3,4,5.但是,对于独立的罗马2-控制数并没有相关结果,所以本章还将给出P2 C n,C3 C n的独立的罗马2-控制数.S2.2预备知识两个简单图G和H的笛卡尔乘积图记作G H,其顶点集为V(G H)= {(u,v):u∈V(G),v∈V(H)},边集为E(G H)={(u1,v1)(u2,v2):u1u2∈E(G),v1=v2或v1v2∈E(H),u1=u2}.下面的两个引理在本章的证明中将会用到.引理2.1[16]若G是一个非平凡的连通图,且γ2(G)=γ(G),则δ(G)≥2.引理2.2[5]对于P n,C n,有γ{R2}(P n)=⌈n+12⌉,γ{R2}(C n)=⌈n2⌉.S2.3独立的罗马2-控制函数的性质命题2.3若G满足i{R2}(G)=γ(G),则有γ2(G)=γ(G).证明.令f=(V0,V1,V2)是图G的一个i{R2}-函数,由罗马2-控制函数的定义可知V1∪V2是G的一个控制集,则γ(G)≤|V1|+|V2|≤|V1|+2|V2|=i{R2}(G).由于i{R2}(G)=γ(G),所以上述不等式链中等号均成立,则有|V2|=0,γ(G)=|V1|.由于V1也是G的一个2-控制集,所以γ2(G)≤|V1|=γ(G).又γ2(G)≥γ(G),因此γ2(G)=γ(G). 命题2.4若G是一个非平凡的连通图,且δ(G)=1,则i{R2}(G)≥γ(G)+1.证明.由引理2.1的逆否命题可知,γ2(G)=γ(G).再由命题2.3的逆否命题可知,i{R2}(G)=γ(G).从而有i{R2}(G)≥γ(G)+1. 定理2.5对于P n,有i{R2}(P n)=⌈n+12⌉.证明.令P n=v1v2...v n.对于v i(1≤i≤n),当i为奇数时,赋值为1,其余点赋值为0.发现:当n为奇数时,我们可以得到P n的一个IR2DF f1,且ω(f1)=n+12.当n为偶数时,只需将v n−1重新赋值为2,其余点不变,也可以得到P n的一个IR2DF f2,且ω(f2)=n+22.从而有i{R2}(P n)≤⎧⎨⎩n+22,n是偶数,n+12,n是奇数.即有i{R2}(P n)≤⌈n+12⌉.反过来,利用引理2.2,由于i{R2}(P n)≥γ{R2}(P n)=⌈n+12⌉.所以i{R2}(P n)=⌈n+12⌉. 定理2.6当n=3时,i{R2}(C3)=2.当n≥4时,有i{R2}(C n)=⎧⎨⎩n2,n是偶数,n+32,n是奇数.证明.令C n=v1v2...v n v1.当n=3时,i{R2}(C3)=2显然成立.下面考虑n≥4的情形.当n为偶数时,对v i(1≤i≤n),当i为奇数时,赋值为1,其余点赋值为0,可得到C n的一个IR2DFℎ1,且ω(ℎ1)=n2.当n为奇数时,对v2,v5赋值为2,对v i(7≤i≤n),当i为奇数时,赋值为1,其余点赋值为0,也可得到C n的一个IR2DFℎ2,且ω(ℎ2)=n+32.从而,当n≥4时,i{R2}(C n)≤⎧⎨⎩n2,n是偶数,n+32,n是奇数.反过来,由引理2.2可知,i{R2}(C n)≥γ{R2}(C n)=⌈n2⌉.令f是C n的一个i{R2}-函数.当n是偶数时,有i{R2}(C n)≥γ{R2}(C n)=n2.而当n是奇数时,由于V1∪V2是独立集,所以不可能出现0,k∈{1,2}交错赋值的情形.即说明一定会出现f(v i)=f(v i+1)=0.进一步,我们可知f(v i−1)=f(v i+2)=2, f(v i−2)=f(v i+3)=0.令P n−6=C n−{v i−2,v i−1,···,v i+3},可知f限制到P n−6上是P n−6的一个IR2DF.再由定理2.5,有i{R2}(C n)=f(C n)=4+f(P n−6)≥4+i{R2}(P n−6)=4+⌈n−6+12⌉=n+32.因此,有i{R2}(C n)≥⎧⎨⎩n2,n是偶数,n+32,n是奇数.从而可证得i{R2}(C n)=⎧⎨⎩n2,n是偶数,n+32,n是奇数.定理2.7对任意的n≥3,有i{R2}(P2 C n)=⎧⎨⎩n,n是偶数, n+1,n是奇数.证明.为了方便叙述,我们记柱形格子图P2 C n的第一行的顶点集为{x1,x2,···,x n},第二行的顶点集为{y1,y2,···,y n}.令C i={x i,y i}表示P2 C n的第i 列,其中1≤i≤n.定义C k={C i:f(C i)=f(x i)+f(y i)=k,1≤i≤n,k= 0,1,2}.显然C0,C1,C2将P2 C n的列划分成了三个部分.定义一个函数g:V(P2 C n)−→{0,1,2},当n是偶数时,令g(x i)= g(y j)=1,其中i≡1(mod2),j≡0(mod2),其余点均赋值为0.当n是奇数时,令g(x1)=g(y3)=2,g(x i)=g(y j)=1,其中i≡0(mod2),j≡1(mod2),i,j≥4.可验证g是P2 C n的一个IR2DF.因此,可知i{R2}(P2 C n)≤⎧⎨⎩n,n是偶数, n+1,n是奇数.反过来,我们假设f=(V0,V1,V2)是P2 C n的一个i{R2}-函数.断言:若存在C i∈C0,则{C i−1,C i+1}⊆C2.证明.若存在C i∈C0,即f(x i)=f(y i)=0.对于点x i,由罗马2-控制函数的定义可知,f(x i−1)=f(x i+1)=1或者f(x i−1)=2或者f(x i+1)=2.若f(x i−1)= f(x i+1)=1,由于V1∪V2是独立集,所以f(y i−1)=f(y i+1)=0.但对于点y i,不满足罗马2-控制函数的定义,矛盾.下面不失一般性,假设f(x i−1)=2,则f(y i−1)=0.对于点y i,由罗马2-控制函数的定义可知,f(y i+1)=2.又V1∪V2是独立集,所以f(x i+1)=0.从而{C i−1,C i+1}⊆C2.由断言可知,对于P2 C n的任意连续的两列C i,C i+1,有f(C i)+f(C i+1)≥2.从而当n是偶数时,有f(V)≥2·n2=n,这时i{R2}(P2 C n)=n.而当n是奇数时,由于V1∪V2是独立集,所以P2 C n的每一列不可能都属于C1∪C2.从而当n是奇数时一定存在一列C属于C0.将C列以及与之相邻的两列都去掉后,剩余偶数列仍满足任意连续两列的函数值之和大于等于2.所以,有f(V)≥2·n−32+4=n+1,这时i{R2}(P2 C n)=n+1. 定理2.8对任意的n≥3,有i{R2}(C3 C n)=⎧⎨⎩n,n≡0(mod3), n+2,n≡1,2(mod3).证明.为了方便叙述,我们记图C3 C n的第一行的顶点集为{x1,x2,···,x n},第二行的顶点集为{y1,y2,···,y n},第三层的顶点集为{z1,z2,···,z n}.令C i= {x i,y i,z i}表示C3 C n的第i列,其中1≤i≤n.定义C k={C i:f(C i)= f(x i)+f(y i)+f(z i)=k,1≤i≤n,k=0,1,2}.定义一个函数g:V(C3 C n)−→{0,1,2},当n≡0(mod3)时,令g(x i)= g(y j)=g(z k)=1,其中i≡1(mod3),j≡2(mod3),k≡0(mod3);当n≡1(mod3)时,令g(x1)=2,g(x i)=g(y j)=g(z k)=1,g(z n−1)=2,g(y n)=1,其中i≡1(mod3),j≡2(mod3),k≡0(mod3),2≤i,j,k≤n−2;当n≡2(mod3)时,令g(x1)=2,g(x i)=g(y j)=g(z k)=1,g(y n)=2,其中i≡1(mod3),j≡2(mod3),k≡0(mod3),2≤i,j,k≤n−1.可验证g 是C3 C n的一个IR2DF.因此,可知i{R2}(C3 C n)≤⎧⎨⎩n,n≡0(mod3), n+2,n≡1,2(mod3).反过来,我们假设f=(V0,V1,V2)是C3 C n的一个i{R2}-函数.断言1.|C0|=0.证明.若存在C i∈C0,即f(x i)=f(y i)=f(z i)=0.不失一般性,对于点y i,由罗马2-控制函数的定义可知,f(y i−1)=f(y i+1)=1或者f(y i−1)=2或者f(y i+1)=2.若f(y i−1)=f(y i+1)=1,则f(x i−1)=f(z i−1)=f(x i+1)= f(z i+1)=0.但对于点x i,z i,并不满足罗马2-控制函数的定义,矛盾.下面不失一般性,我们假设f(y i−1)=2,则f(x i−1)=f(z i−1)=0.对于点x i,z i,由罗马2-控制函数的定义可知,f(x i+1)=f(z i+1)=2.而这与V1∪V2是独立集矛盾.故|C0|=0.由断言1可知,C3 C n的任意一列C,均满足f(C)≥1.从而f(V)=∑︀ni=1f(C i)≥n.因此,当n≡0(mod3)时,可证得i{R2}(C3 C n)=n.下面考虑n≡1,2(mod3)时的情形.断言2.当n≡1,2(mod3)时,|C2|≥2.证明.若|C2|=0,由断言1可知,C3 C n的任一列C,均满足f(C)=1.不失一般性,我们假设f(x i)=f(y i+1)=1,可知f(y i)=f(z i)=f(x i+1)=f(z i+1)=0.对于点z i+1,由罗马2-控制函数的定义可知,f(z i+2)=1,f(x i+2)=f(y i+2)=0.对于点x i+2,同上面的分析,可知f(x i+3)=1,f(y i+3)=f(z i+3)=0.继续下去,我们可推出赋值为1的点的分布规律.下面的讨论中,不妨设f(x i)=f(y j)= f(z k)=1,其中i≡1(mod3),j≡2(mod3),k≡0(mod3),其余点均赋值为0.当n≡1(mod3)时,发现f(x1)=f(x n)=1,这与V1∪V2是独立集矛盾.当n≡2(mod3)时,发现点z1,z n均不满足罗马2-控制函数的定义,矛盾.若|C2|=1,即C3 C n中存在一列C i,使得f(C i)=2,其余列C j(j= i),均满足f(C j)= 1.不妨设f(x i)=2,f(y i+1)=1,同上面的分析,可知f(z i+2)=f(x i+3)=f(y i+4)=1.继续下去,我们可推出赋值为1的点的分布规律.不失一般性,假设f(x1)=2,f(x i)=f(y j)=f(z k)=1,其中i≡1(mod3),j≡2(mod3),k≡0(mod3),i,j,k≥2,其余点均赋值为0.当n≡1(mod3)时,发现f(x1)=2,f(x n)=1,而这与V1∪V2是独立集矛盾.当n≡2(mod3)时,发现点z n不满足罗马2-控制函数的定义,矛盾.从而,当n≡1,2(mod3)时,|C2|≥2.则f(V)≥n−2+4=n+2.因此,当n≡1,2(mod3)时,有i{R2}(C3 C n)=n+2.第三章具有特定独立的罗马2-控制数的图S3.1引言在文献[11]中Henning et al.将罗马2-控制称作“意大利控制”,并用γI 表示意大利控制数.文中,他们刻画了γI(T)=γ(T)+1以及γI(T)=2γ(T)的树.Volkmann在文献[25]中刻画了γ2(G)=γ(G)+1的树,在2011年,Chellali 和Volkmann在文献[7]中又继续刻画了γ2(G)=γ(G)+2的树.Hansberg和Volkmann(2007)在文献[15]证明了任意一个非平凡的连通块图均满足γ2(G)≥γ(G)+1,并且刻画了γ2(G)=γ(G)+1的连通块图.在2008年,他们在[14]中又证明了一个连通的单圈图G,要么满足γ2(G)≥γ(G)+1,要么G=C4.另外,他们还刻画了γ2(G)=γ(G)+1的单圈图.同年,他们在文献[16]中给出了一个图G满足γ2(G)=γ(G)的一些充分条件以及必要条件.特别地,他们还刻画了γ2(G)=γ(G)的仙人掌图.但是,对于具有特定独立的罗马2-控制数的图并没有很好的刻画.由此,本章的主要工作是刻画i{R2}(G)=γ(G)+1的树,单圈图,块图以及仙人掌图.另外,我们也将刻画i{R2}(G)=γ(G)+2的树.S3.2预备知识树是无圈的连通图.若树T恰有两个度至少为2的点,则称T为双星.两个支撑点分别连有r,s个叶子点的双星记作S r,s.图G的剖分图S(G)是通过对G的每一条边uv都添加一个点w,并用uw,wv来代替uv得到的图.对任意正整数r和s,剖分双星S r,s所得到的图,称为剖分双星,记作F r,s.令ℱ={F r,s|r,s≥1}.记双星S r,s的两个支撑点分别为x,y,定义剖分边xy时所添加的那个点为剖分双星F r,s的中心点.剖分星图K1,t的所有边所得到的树,称为健康蜘蛛树,又称为星图剖分图;剖分星图K1,t的至多t−1条边所得到的树,称为病态蜘蛛树.在蜘蛛树T中,定义原星图K1,t的中心为T的头点,与头点距离为2的点称为T的脚点.对于连通图G中一点v∈V(G),若G−v不再是连通图,则称点v是图G 的割点.一个图的冠状图G∘K1是指对每一点v∈V(G),添加一个新的点v′,以及一条悬挂边vv′.若图G中恰含有一个圈,则称该图为单圈图.一个图的块是指该图的没有割点的极大子图.如果一个图的每一个块都是完全图,则称该图为块图.如果图G的每一个块都是圈,则称图G是仙人掌图.对于任意一个非平凡树,我们先用两条平行边替代它的每一条边,然后剖分所有的边,最终所得到的图称作C4-仙人掌图.在本章的证明中,为了方便叙述,我们先给出下面几个记号:我们用T1表示星图剖分图(健康蜘蛛树),用T2表示病态蜘蛛树,用T3表示剖分双星.记树T的叶子点之集为L(T),剖分点之集为B(T),支撑点之集为S(T).令A(T)=V(T)−B(T).当T∈T2且T=P2时,与最大度点相邻的所有叶子点构成的集合记为X(T).显然,X(T)⊆L(T).当T∈T3时,用H(T)表示T的中心点.下面的结果在本章的证明中将会用到.引理3.1[25]若T是一个非平凡树,则γ2(T)≥β(T)+1≥γ(T)+1.引理3.2[25]一个非平凡树T满足γ2(T)=γ(T)+1当且仅当T是星图剖分图,星图剖分图去掉一个叶子点或者双星剖分图.引理3.3[8]一个有n个顶点的树T,满足γ2(T)≥n+1当且仅当T=P1或T2是一个树的剖分图时等号成立.引理3.4[15]若G是一个非平凡的连通块图,则γ2(G)≥γ(G)+1.引理3.5[15]一个非平凡的连通块图G满足γ2(G)=γ(G)+1当且仅当(a)G=H∘K1,其中H是至多有一个割点s的连通块图.(b)G=(H∘K1)−w,其中H或者是只有一个割点s的连通块图且w是H∘K1中与s相邻的一个叶子邻点,或者H与K p同构,p≥2且w是H∘K1中任意一个叶子点.(c)G=(H1∘K1)∪(H2∘K1),其中H1和H2均是至多有一个割点的连通块图(s i)∩且满足存在一点v∈V(G),使得V(H1∘K1)∩V(H2∘K1)={v}=N Hi∘K1L(H i∘K1),这里s i是H i的割点(若没有割点,则s i是H i中的某一个点),i=1,2.(d)G由与K p同构的块图B(p≥3),G1=H1∘K1−w1以及G2=H2∘K1−w2(w i)={s i}=V(G i)∩V(B),i=构成,其中G1,G2与(b)的构造相同,且N Hi∘K11,2,s1=s2(G1,G2也可以是平凡的).为了更好地说明上述引理中不同类型的块图,我们将给出(a)-(d)的样图.引理人掌图.S3.3具有特定独立的罗马2-控制数的树我们先对独立的罗马2-控制数比控制数多1的树进行刻画,然后再对独立的罗马2-控制数比控制数多2的树进行刻画.命题3.7若T⊆ℱ,则i{R2}(T)=γ(T)+1.证明.令T∼=F r,s.注意到T的r+s个叶子点以及中心点构成了一个控制集,记为S.可知S中任意两点间的距离至少是3,显然γ(T)≥|S|.从而有r+s+1≥γ(T)≥|S|=r+s+1.因此γ(T)=r+s+1.将r+s个叶子点以及中心点的两个邻点赋值为1,其他点赋值为0,可得到T的一个IR2DF f,再由命题2.4可知γ(T)+1≤i{R2}(T)≤f(V)=|V1|+2|V2|=r+s+2=γ(T)+1.因此可证得i{R2}(T)=γ(T)+1. 命题3.8若T是一个蜘蛛树,则i{R2}(T)=γ(T)+1.证明.若T是一个健康蜘蛛树,即剖分星图K1,t的所有边所得到的树,易知γ(T)=t.将头点以及t个脚点赋值为1,其余点赋值为0,则可得到T 的一个IR2DF f.再由命题2.4可知,t+1=γ(T)+1≤i{R2}(T)≤f(V)= |V1|+2|V2|=t+1,显然等式成立.若T是一个病态蜘蛛树,不妨假设剖分了星图K1,t的j条边,1≤j≤t−1.易知γ(T)=j+1.将头点赋值为2,j个脚点赋值为1,其余点赋值为0,则可得到T的一个IR2DF g.又由命题2.4可知,j+2=γ(T)+1≤i{R2}(T)≤g(V)=|V1|+2|V2|=j+2,等式成立. 定理3.9一个非平凡树T满足i{R2}(T)=γ(T)+1当且仅当T是星图剖分图,双星剖分图或者病态蜘蛛树.证明.由命题3.7和命题3.8,充分性可证.下面只需证明必要性.设f= (V0,V1,V2)是T的一个i{R2}-函数.由罗马2-控制函数的定义知V1∪V2是T 的一个控制集,则|V1|+|V2|≥γ(T).由于γ(T)+1=i{R2}(T)=f(V)= |V1|+2|V2|≥γ(T)+|V2|,所以|V2|≤1.当|V2|=0时,由罗马2-控制函数的定义知,V0中任意一点至少与V1中的两点相邻,从而可知V1是T的一个2-控制集,所以有|V1|≥γ2(T).再由引理3.1,有γ(T)+1=i{R2}(T)=|V1|≥γ2(T)≥γ(T)+1,所以上述不等式链中等号均成立,即有γ2(T)=γ(T)+1.又由引理3.2可知,T是星图剖分图,星图剖分图去掉一个叶子点或者双星剖分图.而对于星图剖分图去掉一个叶子点所得到的这个图,它的头点x有唯一一个叶子邻点y且f(y)∈{0,1}.若f(y)=0,由f是罗马2-控制函数知,f(x)=2,与|V2|=0矛盾.若f(y)=1,由于|V2|=0,该图的脚点均赋值为1.又由罗马2-控制函数知,f(x)=1,而这与f是独立的矛盾.故当|V2|=0时,T是星图剖分图或者双星剖分图.当|V2|=1时,不妨设V2={u}.由T的连通性知,V0中至少有一个点与点u相邻.由γ(T)+1=i{R2}(T)=f(V)=|V1|+2|V2|=|V1|+|V2|+1知γ(T)=|V1|+|V2|,即说明D=V1∪V2是T的一个γ-集.断言1.V1中任意两点没有公共邻点.反证.假设V1中存在两点v1,v2在V0中至少有一个公共邻点.若至少有两个公共邻点w1,w2,则v1w1v2w2v1是一个圈,与T是树矛盾;若恰好只有一个公共邻点w,令D′=(D∖{v1,v2})∪{w},可知D′也是T的一个控制集.但|D′|<|D|,与D是γ-集矛盾.断言2.u至少有一个私邻点.反证.假设u没有私邻点,即说明与u相邻的点均与V1中的一个点相邻.可重新对u赋值为1,其他点不变,可得到一个新的IR2DF f′.但f′(T)<f(T),这与f是i{R2}-函数矛盾.断言3.V0中的每一个点都与u相邻.对于u的私邻点显然.对于V0中除了u的私邻点以外的点,若都不与u 相邻,则至少与V1中两个点相邻.与断言1矛盾.断言4.V1中的任意一点必定与V0中唯一一个点相邻.反证.由于V1∪V2是独立集,所以V1中的点只能与V0中的点相邻.假设存在V1中的点v与V0中至少两个点z1,z2相邻,由断言3,点z1,z2均与u相邻.则vz1uz2v是一个圈,与T是树矛盾.断言5.V0是独立集.反证.若G[V0]中至少有一条边,记为xy.由断言3,点x,y均与u相邻.则xyu是一个圈,与T是树矛盾.综上可知T是一个病态蜘蛛树.下面我们将对独立的罗马2-控制数比控制数多2的树进行刻画.为了更方便的叙述下面定理的证明,我们首先定义下面几种图类.ℬ1是通过对树T1,T2添加一条路xvwzy得到的集族,其中T1∈T1,T2∈T3,x∈A(T1),y∈A(T2),且x,y中至少有一个点不属于L(T1)∪L(T2)或者x∈L(T1),y∈L(T2),T1=P3.ℬ2是通过对树T1,T2添加一条路xvwzy得到的集族,其中T1∈T1,T2∈T1,x∈A(T1),y∈A(T2).ℬ3是通过对树T1,T2添加一条路xvwzy得到的集族,其中T1∈T3,T2∈T3,x∈A(T1)−L(T1),y∈A(T2)−L(T2).ℬ4是通过剖分树T 0所得到的集族,其中T 0是有3个或4个支撑点,其余点都是叶子点的毛虫树.C 1是通过对树T 1,T 2添加一条边xy 得到的集族,其中T 1,T 2∈T 1∪T 2∪T 3,x ∈B (T 1)−H (T 1),y ∈B (T 2)−H (T 2).C 2是通过对树T 1,T 2添加一条边xy 得到的集族,其中T 1,T 2∈T 1∪T 3,x ∈A (T 1)−L (T 1),y ∈B (T 2).且当y ∈H (T 2)时,T 1只能属于T 1.C 3是通过对树T 1,T 2添加一条边xy 得到的集族,其中T 1∈T 1∪T 3,T 2∈T 1,x ∈B (T 1)−H (T 1),y ∈L (T 2).C 4是通过对树T 1,T 2添加一条边xy 得到的集族,其中T 1∈T 2,T 2∈T 1∪T 3,x ∈X (T 1),y ∈V (T 2)且|X (T 1)|≥2.C 5是通过对树T 1,T 2添加一条边xy 得到的集族,其中T 1∈T 2,T 2∈T 1∪T 2∪T 3,x ∈A (T 1)−L (T 1),y ∈B (T 2)−H (T 2).且当T 1=P 2时,T 2=P 3.C 6是通过对树T 1,T 2添加一条边xy 得到的集族,其中T 1,T 2∈T 2,x ∈X (T 1),y ∈V (T 2)−L (T 2),且|X (T 1)|≥2,T 2=P 2.C 7是通过对树T 1,T 2添加一条边xy 得到的集族,其中T 1,T 2∈T 2,x ∈X (T 1),y ∈X (T 2),且|X (T 1)|≥2,|X (T 2)|≥2.C 8是通过对树T 1,T 2添加一条边xy 得到的集族,其中T 1,T 2∈T 2,x ∈X (T 1),y ∈L (T 2),且|X (T 1)|≥2,T 1=P 3.C 9是通过对树T 1,T 2添加一条边xy 得到的集族,其中T 1∈T 2,T 2=P 2,x ∈B (T 1),y ∈V (T 2),T 1=P 4.定理3.10一个非平凡树T 满足i {R 2}(T )=γ(T )+2当且仅当T ∈ℬ∪C ,其中,ℬ=⋃︀4i =1ℬi,C =⋃︀9i =1C i .证明.设T 是一非平凡的树,且满足i {R 2}(T )=γ(T )+2.令f =(V 0,V 1,V 2)是T 的一个i {R 2}-函数.由于V 1∪V 2是T 的一个控制集,所以γ(T )≤|V 1|+|V 2|.于是,有γ(T )+2=i {R 2}(T )=f (T )=|V 1|+2|V 2|≥γ(T )+|V 2|.从而可知|V 2|≤2.下面分三种情况进行讨论.情形1.|V 2|=0.这时γ(T )=|V 1|−2.情形1.1.G [V 0]中至少有一条边,记为xy .令T x ,T y 分别表示T −{xy }后所得到的两个子树,其中x ∈T x ,y ∈T y ,可知T x ,T y 都是非平凡的.令D x ,D y 分别表示T x ,T y 的一个γ-集,则D x ∪D y 是T 的一个控制集.另外,f 限制到T x ,T y 上也是T x ,T y 的一个IR2DF.从而,有γ(T )≤γ(T x )+γ(T y )≤i {R 2}(T x )−1+i {R 2}(T y )−1≤i {R 2}(T )−2=γ(T ),可知i {R 2}(T x )=γ(T x )+1,i {R 2}(T y )=γ(T y )+1,γ(T )=γ(T x )+γ(T y ).因此,当|V 2|=0时,T x ,T y ∈T 1∪T 3,其中x ∈B (T x ),y ∈B (T y ).而当x ∈H (T x )时,令D ′=(B (T x )∖{x })∪B (T y ),可知D ′是T 的一个控制集.但|D ′|=γ(T x )−1+γ(T y )=γ(T )−1,矛盾.同理,当y ∈H (T y )时,我们依旧可以得到矛盾.因此,T x ,T y ∈T 1∪T 3,其中x ∈B (T x )−H (T x ),y ∈B (T y )−H (T y ).这时,T ∈C 1.情形1.2.V 0是独立集.断言.V 0中的点的度至多为3,且V 0中至多存在一个度为3的点.证明.若V 0中存在一点v ,d (v )≥4.令D ′=(V 1∖N (v ))∪{v },可知D ′是T 的一个控制集.但|D ′|≤|V 1|−4+1=|V 1|−3=γ(T )−1,矛盾.若V 0中存在两个度为3的点v 1,v 2.由于T 是树,所以v 1,v 2至多有一个公共邻点.令D ′=(V 1∖(N (v 1)∪N (v 2)))∪{v 1,v 2},可知D ′是T 的一个控制集.但|D ′|≤|V 1|−5+2=|V 1|−3=γ(T )−1,矛盾.情形1.2.1.V 0中存在一个度为3的点v ,记N (v )∩V 1={x,y,w },可知点x,y,w 的度不可能同时为1.否则T =K 1,3,不满足i {R 2}(T )=γ(T )+2.不失一般性,假设d (x )≥2.令T v ,T x 表示T −{vx }后所得到的两个子树,可知T v ,T x 是非平凡的.由于γ(T )≤γ(T v )+γ(T x )≤i {R 2}(T v )−1+i {R 2}(T x )−1≤i {R 2}(T )−2=γ(T ),所以可得i {R 2}(T v )=γ(T v )+1,i {R 2}(T x )=γ(T x )+1.从而可知当|V 2|=0时,T v ,T x ∈T 1∪T 3,其中v ∈B (T v ),x ∈A (T x ).经进一步分析,当x ∈A (T x )−L (T x )时,T x ,T v ∈T 1∪T 3,v ∈B (T v ).且当v ∈H (T v )时,T x 只能属于T 1.这时,T ∈C 2.当x ∈L (T x )时,T x ∈T 1,T v ∈T 1∪T 3,v ∈B (T v )−H (T v ).这时,T ∈C 3.而对于其他情况,由于均可以找到T 的一个基数为i {R 2}(T )−3的控制集,所以可以排除.情形1.2.2.V 0中每点的度均为2.假设V 1中存在一点v ,d (v )=k ≥2,使得T −N [v ]后可以得到k 个非平凡的子树T 1,T 2,···,T k .令D i 表示T i 的一个γ-集,可知D ′={v }∪D 1∪···∪D k 是T 的一个控制集.所以γ(T )≤|{v }|+∑︀k i =1γ(T i )≤1+∑︀k i =1(i {R 2}(T i )−1)=∑︀k i =1i {R 2}(T i )+1−k ≤i {R 2}(T )−1+1−k =i {R 2}(T )−k =γ(T )+2−k ≤γ(T ).在上述不等式链的第三个不等号处,由于不等号左边没有计算点v 的值,所以在不等号右边需i {R 2}(T )减去1.从而可知上述不等式链中等号均成立,显然这时k=2,i{R2}(T i)=γ(T i)+1,i= 1,2,且γ(T)=γ(T1)+γ(T2)+1.因此,当|V2|=0时,T1,T2∈T1∪T3.记N(v)={x,y},N(x)={x′,v},N(y)={y′,v}.显然x′∈A(T1),y′∈A(T2).若x′∈L(T1),y′∈L(T2),当T1,T2∈T3时,由于可以找到T的一个基数为i{R2}(T)−3的控制集,矛盾.因此,不失一般性,设T1∈T1,T2∈T1∪T3.当|V(T1)|≥5,且T2∈T3时,由于可以找到T的一个基数为i{R2}(T)−3的控制集,矛盾.所以,当T2∈T3时,|V(T1)|=3.这时T∈ℬ1.而当T2∈T1时,T满足i{R2}(T)=γ(T)+2,这时T∈ℬ2.若x′,y′中至少有1个点不是叶子点.当T1,T2∈T1时,T满足i{R2}(T)=γ(T)+2,这时T∈ℬ2.下面只需考虑T1∈T1,T2∈T3或T1∈T3,T2∈T3的情形.对于前者,T是满足i{R2}(T)=γ(T)+2的,这时T∈ℬ1.而对于后者,当x′,y′中有1个点是叶子点时,由于可以找到T的一个基数为i{R2}(T)−3的控制集,矛盾.所以对于后者,x′,y′只能都是非叶子点.这时T∈ℬ3.若找不到这样的点v.我们记V1中度至少为2的点的集合为I,可知对于I中的每一个点x,T−N[x]中至少有一个平凡的分支.因此,V1中的点要么是叶子点,要么与某个叶子点的距离为2.又由于V0中的每个点的度都为2,所以T可以看作是树T0的剖分图,其中树T0中的每个点要么是叶子点,要么是支撑点.令n0=|V(T0)|,可知|V(T)|=n=2n0−1.利用引理3.3可=n0.而当|V2|=0时,由于V1也是T的一个2-控制集,所知,γ2(T)=n+12以|V1|≥γ2(T).于是有γ(T)+2=i{R2}(T)=f(T)=|V1|≥γ2(T).而由引理3.2知,当T/∈T1∪T2∪T3时,有γ2(T)≥γ(T)+2.所以,这时有γ2(T)=γ(T)+2.从而γ(T)=n0−2.断言:T0中的每个支撑点至多与两个支撑点相邻.证明.假设T0中存在一个支撑点y至少与3个支撑点u,v,w相邻.我们用u′,v′,w′表示剖分边yu,yv,yw时所添加的剖分点.由于B(T)是T的一个控制集,且知|B(T)|=n0−1.令D′={y}∪(B(T)∖{u′,v′,w′}),可知D′是T 的一个控制集.但|D′|=1+n0−1−3=n0−3=γ(T)−1,矛盾.如果T0只有一个支撑点,则T剖分星图,不满足i{R2}(T)=γ(T)+2.如果T0有两个支撑点,则T是剖分双星,矛盾.从而可知T0至少有3个支撑点.而当T0至少有5个支撑点时,由断言,我们知道这些支撑点一定是依次相邻的.不失一般性,我们用v1,v2,···,v5表示T0的5个连续的支撑点.用w i表示剖分边v i v i+1(1≤i≤4)时所添加的剖分点.令D′={v2,v4}∪(B(T)∖{w1,w2,w3,w4}),可知D′是T的一个控制集.但|D′|=2+n0−1−4=n0−3=γ(T)−1,矛盾.从而可知T0是有3个或4个支撑点,其余点都是叶子点的毛虫树.这时T∈ℬ4.情形2.|V2|=1.这时γ(T)=|V1|.不妨设V2={u},令S=V1∪V2,可知u一定有S-私邻点.否则,与u相邻的点都与V1中的某个点相邻,可对u重新赋值为1,其余点不变,可得到新的IR2DF f′,但|f′|<|f|,矛盾.对于V0中任意一点x,我们用S x表示x在S中的邻集,即S x=N(x)∩S,且知|S x|≥1.于是对任意两点x,y∈V0,可知|S x∩S y|≤1.否则,将会有圈,与T是树矛盾.情形2.1.G[V0]中至少有一条边,记为xy.这时S x∩S y=φ.若|S x|=|S y|=1,由罗马2-控制函数的定义知,x,y均与u相邻,这时将会有圈,矛盾.若|S x|,|S y|中只有一个为1.不失一般性,若|S x|=1,则x一定与点u相邻.这时x为u 的S-私邻点.令T x,T y为T−{xy}后所得到的两个子树,可知T x,T y都是非平凡的.由于f限制到T x,T y分别是T x,T y的一个IR2DF,且T x的一个γ-集与T y的一个γ-集的并是T的一个控制集.所以,γ(T)≤γ(T x)+γ(T y)≤i{R2}(T x)−1+i{R2}(T y)−1≤i{R2}(T)−2=γ(T).于是上述不等式链中等号均成立,可知i{R2}(T x)=γ(T x)+1,i{R2}(T y)=γ(T y)+1,γ(T)=γ(T x)+γ(T y).因此,T x,T y∈T1∪T2∪T3.由于u∈T x,所以T x∈T2,x∈X(T x),T y∈T1∪T3,y∈B(T y).断言:在T x中,点u至少有两个叶子邻点.证明.若在T x中,点u只有一个叶子邻点,则x为u的唯一的叶子邻点.令D′=B(T x)∪B(T y),可知D′是T的一个控制集,但|D′|=|B(T x)|+|B(T y)|=γ(T x)−1+γ(T y)=γ(T)−1,矛盾.所以,T x∈T2,T y∈T1∪T3,x∈X(T x),|X(T x)|≥2,y∈B(T y).这时T∈C4.若|S x|,|S y|都不为1.同上,依旧令T x,T y为T−xy后所得到的两个子树.可知u∈S x或u∈S y.否则,若u/∈S x∪S y.由T的连通性知,V0中一定存在一点a,满足a∈T x或a∈T y,且au∈E(T).令D′=(V1−N(x)∩V1−N(y)∩V1)∪{x,y,u},可知D′是T的一个控制集.但|D′|≤|V1|−2−2+3=|V1|−1=γ(T)−1,矛盾.不失一般性,我们假设u∈S x,。
关于图的弱罗马控制数的综述
关于图的弱罗马控制数的综述1.1图论的发展简史点与线之间的问题,看似抽象,但是它们在生活中有着很广泛的运用,只需要我们将点与线具象化,与现实中的事物连接起来。
而图论正是研究这些图形问题的一个数学学科分支。
图论作为一门以图为研究对象的学科,在数学的领域中是发展较快的一个重要板块。
首先,我们给定若干的点,再将它们以一定数量的线连接,由此构成的图也就是图论所研究的主要内容,我们可以通过图的形式来刻画现实中的各种事物之间的联系,从而达到图论的应用目的。
图论本身也是属于应用数学的一部分。
图论的起源来自一个非常经典的问题——Konigsberg(柯尼斯堡)问题。
欧拉在1738年用抽象分析法将柯尼斯堡七桥问题(即不重复的通过7座桥的路线)化为图论第一问题并严格证明了该问题无解。
这是属于图论的第一篇论文,是拓扑学研究的开端,从而欧拉通常被认为是拓扑学和图论的始祖。
图的涂色,作为一种常见的问题,是图论的一项重点。
数学家赫伍德曾经成功地用了肯普的方法证明出用五种或更少的颜色为一张图染色的问题。
而最终通过研究者数年的不懈研究,四色问题也得到了解答。
上述问题看似没有很大的使用价值,但是就是这些问题开启了我们对图的思考与研究。
图的控制,在实际运用之中给了人们很大的帮助,也创造出了很大的价值,所以,它是图论研究的重点。
上个世纪50年代末由奥斯坦奥勒(Oystein Ore)和克劳德贝尔赫(Clande Berge)提出并研究了图的控制问题。
而奥勒则是控制术语的率先使用者。
但是一直到1977年,Clemson University的Stephen T Hedetniemi和University of Victoria的Ernie Cockayne合作发表的一篇综述报告中开始使用符号 表示图的控制数,并沿用至今。
这篇文献综述使得控制真正成为许多专家感兴趣的一个研究专题。
目前,图的控制越来越受重视,有了很多很好的成果。
此后,很多不同的参数形式和控制定义被加拿大图论专家Cockayne引入。
关于游戏的英语作文
Games are an integral part of many peoples lives,offering a myriad of benefits and a source of entertainment.Here is an essay exploring the world of games and their impact on individuals and society.The Allure of Games:A Gateway to Fun and LearningIn the digital age,games have transcended the boundaries of mere entertainment to become a cultural phenomenon.They are not just a pastime but a multifaceted experience that engages players on various levels.The Evolution of GamingThe history of games dates back to ancient civilizations,where board games were played for strategy and leisure.With the advent of technology,video games emerged,offering interactive experiences that could be enjoyed in the comfort of ones home.From the simple pixelated graphics of early consoles to the realistic renderings of modern gaming, the evolution of games has been nothing short of revolutionary.Types of GamesGames come in a multitude of genres,catering to diverse interests and age groups.Action games provide adrenalinepumping excitement,while puzzle games challenge the mind and improve cognitive skills.Roleplaying games RPGs immerse players in rich narratives and complex worlds,allowing them to assume different identities and make decisions that shape the games outcome.The Benefits of GamingGaming offers numerous benefits beyond mere entertainment.It can enhance problemsolving abilities,improve handeye coordination,and foster strategic thinking. Moreover,multiplayer games promote social interaction and teamwork,as players collaborate to achieve common goals.The Impact on SocietyThe influence of games on society is profound.They have become a significant part of popular culture,inspiring movies,merchandise,and even academic studies.The gaming industry has also created job opportunities in areas such as game design,programming,and marketing.Challenges and ConcernsDespite the positive aspects,gaming also faces criticism.Concerns about excessive screen time,addiction,and the potential for violent content in games are valid considerations.It is essential for players,especially young ones,to maintain a balanced lifestyle and engage in other activities besides gaming.The Future of GamingAs technology advances,the future of gaming looks promising.Virtual reality VR and augmented reality AR are set to transform the gaming landscape,offering more immersive and interactive experiences.The integration of artificial intelligence AI will further enhance game dynamics,creating more adaptive and challenging gameplay. ConclusionGames are more than just a form of entertainment they are a cultural force that shapes and reflects society.As we navigate the digital landscape,it is crucial to appreciate the value of games while being mindful of their potential pitfalls.By doing so,we can ensure that gaming remains a positive and enriching part of our lives.。
使用刚体约束制作多物体互动
使用刚体约束制作多物体互动使用Blender软件中的刚体约束功能,可以轻松制作出多个物体之间的互动效果。
刚体约束可以模拟现实中物体之间的各种关系,比如碰撞、连接、固定等,让物体之间更加真实地互动起来。
首先,我们需要创建多个物体,可以是各种形状和大小的物体。
选择一个物体,在属性编辑器中切换到“物理”选项卡。
在“刚体”栏中,将类型设置为“主动”,表示该物体是一个主动物体,受到其他物体的影响。
接下来,我们需要给该物体添加刚体约束。
选择一个物体,在属性编辑器中切换到“约束”选项卡。
点击“添加约束”按钮,在弹出的菜单中选择适合的约束类型。
比如,选择“固定约束”可以将该物体固定在某个位置,选择“弹簧约束”可以模拟弹簧的效果,选择“球形约束”可以模拟两个物体之间的关节等。
添加约束后,我们还可以对约束进行调整。
在约束列表中,可以设定约束的参数,比如弹簧的刚度、长度等。
通过调整这些参数,可以达到不同的互动效果。
在制作多物体互动的过程中,还可以使用其他功能来增强效果。
比如,可以使用碰撞检测功能来模拟物体之间的碰撞效果。
在属性编辑器中切换到“碰撞”选项卡,选择合适的碰撞类型,比如“网格”或“凸包”。
然后,将其他物体设置为被动物体,表示它们不会主动移动,只会被其他物体影响。
通过以上步骤,我们可以制作出多物体之间真实的互动效果。
可以进行各种不同形式的实验和模拟,比如模拟物体掉落、弹簧振动、碰撞反应等。
除了上述基本的刚体约束功能,Blender软件还提供了更多高级的约束选项。
比如,可通过“路径约束”将物体沿特定路径移动,可通过“目标约束”将物体朝向另一个物体等。
这些高级约束功能可以用来制作更复杂的互动效果,让物体之间的关系更加精确和灵活。
总结来说,使用Blender软件中的刚体约束功能,可以轻松制作多物体之间的互动效果。
通过选择合适的约束类型,调整约束参数,以及利用其他功能增强效果,可以制作出各种真实的模拟和实验。
只需简单的几步操作,就能让物体之间互动起来,为创造各种有趣场景和效果提供了强大的工具。
无尽滑雪scratch编程作品
无尽滑雪scratch编程作品
今天给大家分享的Scratch作品是《无尽滑雪大作战》,这是一款躲避小游戏。
游戏的目标就是躲过障碍物,收集足够的金币,获得胜利。
点击绿旗,运行程序,启动游戏,在舞台的顶部,会随机出现各种障碍物和金币,从舞台上方开始向下运动,直到碰到舞台下边缘消失。
点击滑雪人,滑雪人就开始向右移动,然后可以通过按下左右键改变滑雪人的运动方向,在滑雪的过程中,要尽力避开障碍物,同时收集金币。
如果碰到树桩、小熊或者炸弹则挑战失败,如果碰到金币,则加10分,当分数超过50时,挑战成功。
当然,挑战成功的条件你可以自由指定,比如100分,200分。
各角色效果简单说明如下:滑雪人:默认显示在舞台底部中间位置,使用鼠标点击一下就开始向右移动,如果碰到舞台边缘或是障碍物,则结束游戏,挑战失败,按下键盘上的←键,滑雪人就向左移动,按下键盘上的→键,滑雪人就向右移动;障碍物:从舞台上边缘随机位置出现,向下运动直到舞台下边缘消失,包括金币、小熊、树桩和炸弹4个不同的造型,其中金币是滑雪人要收集的,而其它3个则要躲避;结果:包括挑战成功和挑战失败两个造型,以及相应的音效;滑雪bg:通过两个相同的滑雪bg角色来实现无限向下滚动效果,让人赶紧是滑雪人向前滑雪的效果。
cccd包的说明文档说明书
Package‘cccd’October12,2022Version1.6Date2022-04-08Title Class Cover Catch DigraphsAuthor David J.Marchette<********************>Maintainer David J.Marchette<********************>Depends igraphImports proxy,deldir,FNNSuggests MatrixDescription Class Cover Catch Digraphs,neighborhood graphs,andrelatives.License GPL(>=2)Repository CRANDate/Publication2022-04-0812:22:29UTCNeedsCompilation noR topics documented:cccd (2)ccd (5)dominate (6)gg (7)juggling (8)nng (10)prune (11)rng (12)Index1512cccd cccd Class Cover Catch DigraphDescriptionConstructs a class cover catch digraph from points or interpoint distance matrices.Usagecccd(x=NULL,y=NULL,dxx=NULL,dyx=NULL,method=NULL,k=NA,algorithm= cover_tree )cccd.rw(x=NULL,y=NULL,dxx=NULL,dyx=NULL,method=NULL,m=1,d=2)cccd.classifier(x,y,dom.method= greedy ,proportion=1,...)cccd.classify(data,C,method=NULL)cccd.classifier.rw(x,y,m=1,d=2)cccd.multiclass.classifier(data,classes,dom.method= greedy ,proportion=1,...) cccd.multiclass.classify(data,C,method=NULL)##S3method for class cccdplot(x,...,plot.circles=FALSE,dominate.only=FALSE,D=NULL,vertex.size=2,bel=NA,vertex.color="SkyBlue2",dom.color="Blue",ypch=20,ycex=1.5,ycol=2,use.circle.radii=FALSE,balls=FALSE,ball.color=gray(0.8),square=FALSE,xlim,ylim)##S3method for class cccdClassifierplot(x,...,xcol=1,ycol=2,xpch=20,ypch=xpch,balls=FALSE,add=FALSE)Argumentsx,y the target class and non-target class points.Either x,y or dxx,dyx must be pro-vided.In the case of plot,x is an object of class cccd.dxx,dyx interpoint distances(x against x and y against x).If these are not provided they are computed using x and y.method the method used for the distance.See dist.dom.method,proportionthe method used for the domination set computation,and the proportion ofpoints required to dominate.See dominate.k If given,get.knn is used from FNN to approximate the class cover catch graph.Each x covers no more than the k nearest neighbors to it.This will be muchfaster and use less memory for large data sets,but is an approximation unless kis sufficiently large.algorithm See get.knn.m slope of the null hypothesis curvedata data to be classifiedcccd3d dimension of the dataclasses class labels of the dataC cccd objectplot.circles logical.Plot the circles around the points if TRUE.dominate.only logical.Only plot the digraph induced by the dominating set.D a dominating set.Only used if dominate.only is TRUE.If dominate.only isTRUE and D is NULL,then dominate is called.vertex.size,vertex.color,bel,dom.colorparameters controling the plotting of the vertices.dom.color is the color of thevertices in the dominating set.balls,ball.colorif balls=TRUE,the cover is plotted asfilled balls,with ball.color controlingtheir color.In the cass of cccdClassifier,balls can be"x"or"y"indicatingthat only one of the balls should be plotted.ypch,ycex,ycol parameters for plotting the non-target points.xpch,xcol parameters for plotting thefirst class points.add logical.Should the classifier plot be added to an existing plot?use.circle.radiilogical.Ensure that the circlesfit within the plot.square logical.Make the plot square.xlim,ylim if present,these control the plotting region....arguments passed to cccd or plot.DetailsThe class cover catch digraph is a graph with vertices defined by the points of x and edges de-fined according to the balls B(x,d(x,Y)).There is an edge between vertices x1,x2if x2∈B(x1,d(x1,Y)).If dyx is not given and the method is’euclidean’,then get.knnx is used tofind the nearest y to each x.If k is given,only the k nearest neighbors to each point are candidates for covering.Thus the cccd will be approximate,but the computation will(generally)be faster.Since get.knn uses Euclidean distance,these choices will only be valid for this distance metric.Since the graph will tend to be larger than otherwise,the dominating set computation will be slower,so one should trade-off speed of calculation,approximation,and the proportion option to the dominating set(which can make that calculation faster at the cost of returning a subset of the dominating set).Valuean object of class igraph.In addition,it contains the attributes:R a vector of radii.Y the y vectors.layout the x vectors.In the case of the classifier,the attributes are:Rx,Ry vectors of radii.Cx,Cy the ball centers.4cccd NoteThe plotting assumes the cccd used Euclidean distance,and so the balls/circles will be Euclidean balls/circles.If the method used in the distance was some other metric,you’ll have to plot the balls/circles yourself if you want them to be correct on the plot.Author(s)David J.Marchette,************************ReferencesD.J.Marchette,"Class Cover Catch Digraphs",Wiley Interdisciplinary Reviews:ComputationalStatistics,2,171-177,2010.D.J.Marchette,Random Graphs for Statistical Pattern Recognition,John Wiley&Sons,2004.C.E.Priebe,D.J.Marchette,J.DeVinney and D.Socolinsky,"Classification Using Class CoverCatch Digraphs",Journal of Classification,20,3-23,2003.See Alsoccd,rng,gg,dist,get.knn dominateExamplesset.seed(456330)z<-matrix(runif(1000),ncol=2)ind<-which(z[,1]<.5&z[,2]<.5)x<-z[ind,]y<-z[-ind,]g<-cccd(x,y)C<-cccd.classifier(x,y)z2<-matrix(runif(1000),ncol=2)ind<-which(z2[,1]<.5&z2[,2]<.5)cls<-rep(0,nrow(z2))cls[ind]<-1out<-cccd.classify(z2,C)sum(out!=cls)/nrow(z2)##Not run:plot(g,plot.circles=TRUE,dominate.only=TRUE)points(z2,col=2*(1-cls)+1,pch=20)##End(Not run)ccd5 ccd Cluster Catch DigraphsDescriptionconstruct the cluster catch digraph from a data matrix.Usageccd(data,m=1,alpha=0.05,sequential=TRUE,method=NULL)##S3method for class ccdplot(x,...)Argumentsdata a matrix of observations.m slope of the null hypothesis curve.alpha alpha for the K-S test if sequential=T.sequential use the sequential or non-sequential version.method the method used for the distance.See dist.x an object of class ccd....arguments passed to cd.Detailscluster cover d is just a call to cd.Valuean object of class igraph.In addition,this contains the attributes:R the radii.stats the K-S statistics.layout the data vectors.walks the y-values of the random walks.fs the null hypothesis curve.A the adjacency matrix.m,alpha arguments passed to ccd.Author(s)David J.Marchette************************6dominateReferencesD.J.Marchette,Random Graphs for Statistical Pattern Recognition,John Wiley&Sons,2004.See AlsocccdExamplesx<-matrix(rnorm(100),ncol=2)G<-ccd(x)##Not run:plot(G)##End(Not run)dominate Dominating SetsDescriptionfind maximum dominating sets in(di)graphs.Usagedominate(g,method="greedy",proportion=1.0)Argumentsg an adjacency matrix.method one of"greedy","random","byRadius","greedyProportion".proportion proportion of points to cover.Detailsdominate is the main program which calls the others,as indicated by method.Greedy is the greedy dominating algorithm.In the greedy method ties are broken byfirst index(a la which.max).The byRadius method uses the radii to break ties while the random routine breaks ties randomly.If proportion is given,the algorithm stops after proportion points are covered.Valuea vector of vertices corresponding to the dominating set.Author(s)David J.Marchette************************gg7ReferencesT.W.Haynes,S.T.Hedetniemi and P.J.Slater,Fundamentals of Domination in Graphs,Marcel Dekker,1998,Examplesx<-matrix(runif(100),ncol=2)y<-matrix(runif(100,-2,2),ncol=2)G<-cccd(x,y)D<-dominate(G)##Not run:plot(G,balls=TRUE,D=D)##End(Not run)gg Gabriel GraphDescriptionA Gabriel graph is one where the vertices are points and there is an edge between two points if themaximal ball between the points contains no other points.Usagegg(x,r=1,method=NULL,usedeldir=TRUE,open=TRUE,k=NA,algorithm= cover_tree )Argumentsx a matrix of observations.r a multiplier on the ball radius.method the method used for the distance.See distusedeldir logical.Whether to use the deldir package or not.open logical.If TRUE,open balls are used in the definition.k If given,get.knn is used from FNN to approximate the Gabriel graph.Only the k nearest neighbors to the points are used to determine whether an edge shouldbe made or not.This will be much faster and use less memory for large datasets,but is an approximation unless k is sufficiently large.algorithm See get.knn.Detailsplaces an edge between two points i,j if the ball centered between the points with radius rd(i,j)/2 contains no other points.Valuean object of class igraph.In addition it contains the attributes:layout the data.r,p arguments passed to ggAuthor(s)David J.MarchetteReferencesK.R.Gabriel and R.R.Sokal,A New Statistical Approach to Geographic Variation Analysis,Sys-temic Zoology,18,259-278,1969D.J.Marchette,Random Graphs for Statistical Pattern Recognition,John Wiley&Sons,2004.See Alsorng,dist,get.knnExamplesx<-matrix(runif(100),ncol=2)g<-gg(x)##Not run:plot(g)##End(Not run)juggling JugglingDescriptiona resampled version of the CCCD classifier.Usagejuggle(data,classes,sampled=TRUE,sample.dim=FALSE,num=100,sample.proportion=0.1,k=2,method=NULL) juggle.classify(data,J,tdata,indices)Argumentsdata,tdata training data from which to build the classifier.In the case of juggle.classify, tdata is the training data and data is the test data.classes class labels.sampled whether the data are subsampled.sample.dim if TRUE,the dimensions(variates)are also sampled.num number of juggles(resamples).sample.proportionproportion of the data to sample.If1or greater,the data are sampled withreplacement.k number of variates to sample when sample.dim is TRUE.J the juggled classifier.indices the indices of the juggles to use.method the method used for the distance.See distDetailsThe idea of juggling is to sample the data,compute a CCCD classifier,then repeat.The resampling is controled by the two sampling variables,which basically determine whether the data are sampled with replacement,or whether a subsample is used.If sample.dim is TRUE,the variates are also sampled,with k indicating how many are sampled.Valuejuggle.classify returns a matrix holding the classification probabilities for each observation in data.a list consisting of:S the dominating sets.R the radii.dimension the dimension of the data.vars in the case of sample.dim=TRUE,the variables sampled each time.Only the indicies into the training data are stored in J,which is why the classifier requires the original training data in tdata.Author(s)David J.Marchette,************************See Alsocccd,dist10nng nng Nearest Neighbor GraphsDescriptionnearest neighbor,k-nearest neighbor,and mutual k-nearest neighbor(di)graphs.Usagenng(x=NULL,dx=NULL,k=1,mutual=FALSE,method=NULL,use.fnn=FALSE,algorithm= cover_tree )Argumentsx a data matrix.Either x or dx is requireddx interpoint distance matrixk number of neighborsmutual logical.if true the neighbors must be mutual.See details.method the method used for the distance.See distuse.fnn logical.If TRUE,get.knn from the FNN package is used to obtain the neigh-bors.algorithm see get.knn.Detailsa k-nearest neighbor graph is a digraph where each vertex is associated with an observation andthere is a directed edge between the vertex and it’s k nearest neighbors.A mutual k-nearest neighbor graph is a graph where there is an edge between x and y if x is one of the k nearest neighbors of y AND y is one of the k nearest neighbors of x.Valuean object of class igraph with the extra attributeslayout the x vectors.k,mutual,p arguments given to nn.Author(s)David J.Marchette************************ReferencesD.J.Marchette,Random Graphs for Statistical Pattern Recognition,John Wiley&Sons,2004.prune11 See Alsodist get.knnExamplesx<-matrix(runif(100),ncol=2)G1<-nng(x,k=1)##Not run:par(mfrow=c(2,2))plot(G1)##End(Not run)G2<-nng(x,k=2)##Not run:plot(G2)##End(Not run)G5<-nng(x,k=5)##Not run:plot(G5)##End(Not run)G5m<-nng(x,k=5,mutual=TRUE)##Not run:plot(G5m)par(mfrow=c(1,1))##End(Not run)prune Prune PointsDescriptiona nearest neighbor pruning using neighborhood graphs.Usageprune(x,classes,prox="Gabriel",ignore.ties=TRUE,...)12rng Argumentsx a data matrix.classes a vector of class labels.prox type of proximity graph.ignore.ties do not prune if there is a tie vote....arguments passed to the proximity graph.DetailsFirst a proximity graph is computed on the data.Then points are marked if their neighbors havea different class than they do:if the most common class among the neighbors is different than thepoint.Then all marked points are removed.ValueA list with attributes:x the pruned data.v the indices of the retained data.g the proximity graph.Author(s)David J.Marchette,************************Referenceshttp://www.bic.mni.mcgill.ca/users/crisco/pgedit/rng Relative Neighborhood Graph.Descriptionthe relative neighborhood graph defined by a set of points.Usagerng(x=NULL,dx=NULL,r=1,method=NULL,usedeldir=TRUE,open=TRUE,k=NA, algorithm= cover_tree )rng13Argumentsx a data matrix.Either x or dx must be provided.dx an interpoint distance matrix.r a multiplier to grow the balls.method the method used for the distance.See distusedeldir a logical.If true and the data are two dimensional and the deldir package is installed,the Delaunay triangularization isfirst computed,and this is used tocompute the relative neighborhood graph.open logical.If TRUE,open balls are used in the definition.k If given,get.knn is used from FNN to approximate the relative neighborhood graph.Only the k nearest neighbors to the points are used to determine whetheran edge should be made or not.This will be much faster and use less memoryfor large data sets,but is an approximation unless k is sufficiently large.algorithm See get.knn.Detailsthe relative neighborhood graph is defined in terms of balls centered at observations.For two observations,the balls are set to have radius equal to the distance between the observations(or r times this distance if r is not1).There is an edge between the vertices associated with the observations if and only if there are no vertices in the lune defined by the intersection of the balls.Theflag open should make no difference for most applications,but there are very specific cases (see the example section below)where setting it to be TRUE will give the wrong answer(thanks to Luke Mathieson for pointing this out to me).Valuean object of class igraph,with the additional attributeslayout the x matrix.r,p arguments given to rng.Author(s)David J.Marchette************************ReferencesJ.W.Jaromczyk and G.T.Toussaint,"Relative neighborhood graphs and their relatives",Proceed-ings of the IEEE,80,1502-1517,1992.G.T.Toussaint,"A Graph-Theoretic Primal Sketch",Computational Morphology,229-260,1988.D.J.Marchette,Random Graphs for Statistical Pattern Recognition,John Wiley&Sons,2004. See Alsogg,cccd,ccd,dist get.knn14rngExamplesx<-matrix(runif(100),ncol=2)g<-rng(x)##Not run:plot(g)##End(Not run)##Example using open :g<-graph.full(5,directed=FALSE)g1<-rng(x=get.adjacency(g,sparse=FALSE),open=TRUE)ecount(g1)g2<-rng(x=get.adjacency(g,sparse=FALSE),open=FALSE)graph.isomorphic(g2,g)Index∗graphscccd,2ccd,5dominate,6gg,7juggling,8nng,10prune,11rng,12cccd,2,6,9,13ccd,4,5,13dist,2,4,5,7–11,13dominate,2,4,6get.knn,2,4,7,8,10,11,13gg,4,7,13juggle(juggling),8juggling,8nng,10cd(cccd),2cdClassifier(cccd),2d(ccd),5prune,11rng,4,8,1215。
关于几类图的Fractional全控制数
On Fractional Total Domination Numbers in Graphs 作者: 徐保根 赵丽鑫 邹妍
作者机构: 华东交通大学理学院数学系,南昌330013
出版物刊名: 宜春学院学报
页码: 1-3页
年卷期: 2014年 第12期
主题词: 全控制数 Fractional全控制函数 完全t—部图 联图
摘要:设G=(V,E)是一个无孤立点的图,一个实值函数f:V→[0,1]满足
∑v∈N(u)f(v)≥1对一切u∈V(G)都成立,则称f为图G的一个Fractional全控制函数。
图
的Fractional全控制数定义为γ0f()G=min{f(V)|f为图G的Fractional全控制函数},文章中研究了图的Fractional全控制问题,主要给出了关于联图的Fractional全控制数的一个上界,由此确定了几类特殊图的Fractional全控制数,并推广了部分已知结果。
图的圈符号控制数
图的圈符号控制数徐保根;康洪波;赵利芬;操叶龙【摘要】Let G =(V,E)be a graph,a function f:V→{-1 ,1}is said to be a cycle signed domination function (CSDF)of G if∑f(v)≥1 holds for any induced cycle C of G ,where the cycle signed domi-v∈V(C) nation number of G is defined asγsc(G)=min{∑v∈V f(v) fis a CSDF of G}.Some lower bounds ofthe cycle signed domination number of a graph are obtained,and all graphs G withδ≥2 andγsc(G)=4 -V(G) are characterized.%设G =(V,E)是一个图,一个函数f:V→{-1,1}如果满足∑f(v)≥1对G中每一个导出圈C均成v∈V(C)立,则称f为图G的一个圈符号控制函数,图G的圈符号控制数定义为γsc(G)=min{∑f(v):f为图G的一个圈v∈V(G)符号控制函数}。
得到了图的圈符号控制数的若干下界,并刻划了满足δ≥2且γsc (G)=4- V (G)的所有图。
【期刊名称】《中山大学学报(自然科学版)》【年(卷),期】2013(000)006【总页数】3页(P136-138)【关键词】图;符号控制;圈符号控制函数;圈符号控制数【作者】徐保根;康洪波;赵利芬;操叶龙【作者单位】华东交通大学基础科学学院,江西南昌331013;华东交通大学基础科学学院,江西南昌331013;华东交通大学基础科学学院,江西南昌331013;华东交通大学基础科学学院,江西南昌331013【正文语种】中文【中图分类】O157.5本文中所指的图均为无向简单图,文中未说明的符号和术语同于文献[1]。
关于图的集控制数
关于图的集控制数徐保根;罗茜;丁宗鹏【摘要】Let G=(V,E) be a graph, if the set V(G) may be partitioned into t disjoint dominating set, then G has a t -domination partition. The domatic number d(G) of G is defined as d(G)=max. {t | G has a t -domination partition}. In this paper, we study the domatic number problems for the product graph and the join graph, some bounds of the domatic numbers, and determined the domatic number for some special graphs are obtained.%设G是一个图,如果V(G)能划分为t个两两不交的控制集Dt(i=1,2,…,t),则称G有t-控制集划分.图G的集控制数定义为d(G)=max{ t|G有t-控制集划分}.该文主要研究乘积图与联图的集控制问题,给出其集控制数的界限,并确定一些特殊图的集控制数.【期刊名称】《华东交通大学学报》【年(卷),期】2011(028)005【总页数】4页(P1-4)【关键词】图;乘积图;联图;控制集;集控制数【作者】徐保根;罗茜;丁宗鹏【作者单位】华东交通大学基础科学学院江西南昌330013;华东交通大学基础科学学院江西南昌330013;华东交通大学基础科学学院江西南昌330013【正文语种】中文【中图分类】O157.51 引言及定义文中所指的图均为无向简单图,文中未说明的符号和术语同文献[1]。
设G为一个图,对于任意v,则NG(v)表示v点在G中的邻域,dG(v)= ||NG(v)表示v点在G中的度,NG[v]=NG(v)∪{v}称为v点的闭邻域,δ和Δ分别为图G 的最小度和最大度,有时,NG[v]和dG(v)分别简记为 N[v]和d(v)。
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Domination Games on Infinite GraphsReinhard Diestel and Imre LeaderWe consider two infinite games,played on a countable graph G givenwith an integer vertex labelling.One player seeks to construct a ray(a one-way infinite path)in G,so that the ray’s labels dominate orelude domination by an integer sequence being constructed by anotherplayer.For each game,we give a structural characterization of thegraphs on which one player or the other can win,providing explicitwinning strategies.1.IntroductionLet G be a countable graph,and let :V(G)→ωbe an injective labelling of its vertices with natural numbers(thus distinct vertices have distinct labels). Consider the following game for two players,Adam and Eve.The two players move alternately,ωtimes,Eve having thefirst move.When Eve moves,she plays a natural number;when Adam moves,he plays a vertex of G.In the course of one game,Eve thus creates a sequence e:ω→ω,n→e n,of numbers, while Adam creates a sequence a:ω→V(G),n→a n,of vertices.More specifi-cally,Adam tries to choose his vertices so as to define a ray(a one-way infinite path)in G,i.e.so that a n+1is adjacent to a n for every n∈ωand no vertices are repeated.Let us say that a sequence(a n)n∈ωof natural numbers dominates another such sequence(b n)n∈ωif a n b n for all n greater than some n0∈ω.In the dominating game,Adam wins if his function a defines a ray whose sequence ( (a n))of labels dominates Eve’s sequence(e n).Otherwise,Eve wins.In the bounding game,Adam merely tries to escape domination by Eve:he wins iffhe constructs a ray whose labels exceed the corresponding terms of Eve’s sequence again and again,i.e.such that(e n)does not dominate( (a n)).Note that if Eve has won a particular instance of the bounding game,this same game would also go to her credit if viewed as an instance of the dominating game.Similarly, if Adam can win the dominating game on a particular graph,he can trivially also win the bounding game on that graph.Let us look at a few examples.It is easy to see that Adam has a winning strategy for the dominating game on Tω,the tree in which every vertex has countably infinite degree.Indeed,he can alwaysfind a new vertex a n+1adja-cent to his previous vertex a n and such that (a n+1)>e n+1.This,of course, also gives him a winning strategy for any graph that contains a copy of Tωas a subgraph.In Section2,we shall prove that this simple example already exhausts Adam’s resources for the dominating game.More precisely,we shall show that Adam has a winning strategy for the dominating game on G if and only if Tω⊂G,and that otherwise Eve has a winning strategy.The proof of this result will be fairly straightforward.In contrast,the situation for the bounding game is rather more interesting. Again,Adam clearly has a winning strategy on Tω.But more is true:since Adam only needs to beat Eve’s sequence again and again,he will also win on any subdivision of Tω,i.e.on any graph obtained from Tωby replacing its edges with non-trivial paths whose interiors are pairwise disjoint.Any such graph will be called a T Tω.F IGURE1.The prototype bundle graph BFor similar reasons,Adam has a winning strategy on the graphs B and F shown in Figs.1and2.Indeed,he simply constructs a ray from left to right, starting at the leftmost vertex(of B or F,respectively).Provided he never moves back towards the left on B or vertically up on F,he will again and again find himself at a vertex with an infinite choice of neighbours to the right:as all these neighbours carry different labels,he can choose one whose label exceeds the corresponding number just played by Eve.As before,Adam’s winning strategies for B and F extend to subdivisions of these graphs;subdivisions of B will be called bundle graphs,subdivisions of F are fan graphs.F IGURE2.The prototype fan graph FIn Section3,we shall show that these three types of subgraph provide the unique discriminator between the graphs where Adam has a winning strategy and those where Eve can win.In other words,we shall prove that Adam has a winning strategy for the bounding game on G if and only if G has a subgraphisomorphic to a T Tω,a bundle graph or a fan graph,and that otherwise Eve has a winning strategy.Note that,for the domination game as for the bounding game,our char-acterizations depend only on the structure of G,and not on the particular labelling chosen.For afixed countable graph G with labelling ,each game is Borel(meaning that the set of winning runs is Borel in the obvious product topology),and so it follows from Martin’s theorem of Borel determinacy[3]that one player or the other must have a winning strategy.(In fact,each of our games is Fσ,so this follows already from Wolfe’s theorem on Fσdeterminacy[4].)However, we shall not need to rely on this result:we shall always be able to give explicit winning strategies.Let us remark in passing that a typical winning strategy is unlikely to depend on the entire information encoded in the positions to which it assigns a next vertex or number.In order to make the game set-up described above precise,we now briefly go through the(standard)definitions of the terms involved.The reader familiar with infinite games may wish to skip through to the start of the next section.Let G be afixed countable graph whose vertices are injectively labelled with natural numbers.For either game,a position of the game will be a pair of a sequence v0,...,v n of vertices of G(‘those which Adam has played so far’) and a sequence k0,...,k m of natural numbers(‘those which Eve has played so far’)such that either n=m or n=m−1(depending on‘who is to move next’).A strategy for Adam is a functionαwhich assigns to every position with n=m−1a vertex of G.A strategy for Eve is a functionηwhich assigns to every position with n=m a natural number.A run of the game is a pair ofω-sequences(a n)and(e n).Adam has played this run according to the strategyαif a n=α(a0,...,a n−1|e0,...,e n)for every n∈ω.Similarly,Eve has played this run according to the strategyηif e n=η(a0,...,a n−1|e0,...,e n−1)for every n∈ω.A winning strategy(for either Adam or Eve)is a strategy such that every run on G played according to it is won.2.The dominating gameWe start by showing that,for the dominating game,Adam can force a win only if G⊇Tω.Proposition1.Adam has a winning strategy for the dominating game on G if and only if Tω⊂G.Proof.As we saw in Section1,Adam has an obvious winning strategy if G⊇Tω:he is easily able to beat Eve at every move.So it remains for us to show that if Adam has a winning strategy then G⊇Tω.Let Adam’s winning strategy beα.We claim that there exists a sequence e1,...,e k of natural numbers such that for every extension e1,...,e n(n k) we have a n e n when Eve plays e1,...,e n and Adam followsα.Indeed,if this were not the case then we could inductively construct an infinite sequence e1,e2,...such that if Eve plays this sequence and Adam followsαthen a n<e n for infinitely many n.However,this is impossible,asαis a winning strategy for Adam.Now consider the subgraph H of G spanned by Adam’s replies(followingα) to all the sequences starting e1,...,e k.By the choice of e1,...,e k,it is clear that,for every such sequence e1,...,e n(n k),Adam must have an infinite choice of distinct replies to the sequences e1,...,e n,x as x varies overω.Thus H is a(non-empty)graph in which every vertex has infinite degree.However, in any such graph it is easy to construct a Tωinductively.As we remarked earlier,Proposition1implies by Borel(or just Fσ)deter-minacy that Eve has a winning strategy for the dominating game on any graph not containing a Tω.In the proof of the following extension of Proposition1, we make such a winning strategy explicit.Theorem2.If Tω⊂G then Adam has a winning strategy for the dominating game on G.Otherwise,Eve has a winning strategy.Proof.We assume that G contains no Tω,and construct a winning strategy for Eve.We start by recursively defining a rank functionρon some or all of the vertices of G.For each ordinalα,give rankα=ρ(v)to all vertices v such that all butfinitely many neighbours w of v have rankρ(w)<α.If any vertex remains unranked,then it has infinitely many unranked neighbours,and so the unranked vertices span a(non-empty)graph in which every vertex has infinite degree.We may then construct a Tω⊂G from these vertices inductively.Thus, since G⊇Tωby assumption,ρgets defined for every vertex of G.We may now choose a winning strategy for Eve as follows.Let Eve’sfirst move be arbitrary(say0).Later,if Adam’s last chosen vertex is v,let Eve play the number1+max{ (w)|w is a neighbour of v andρ(w) ρ(v)};note that,by definition ofρ(v),this maximum is taken over just afinite set.Now consider a run of the game which Eve has played according to this strategy.If Adam fails to construct a ray,then Eve wins by definition.So assume that Adam does indeed construct a ray R⊂G.Since there is no infinite descending sequence of ordinals,R has infinitely many vertices each of whose rank is at most that of its successor on R.But Eve beats Adamon all these successors,so Adam’s sequence( (a n))fails to dominate Eve’ssequence(e n).Thus Eve’s strategy is indeed a winning strategy.3.The bounding gameWe now turn our attention to the bounding game.It turns out that the keynotion here is that of a propagating set of paths[1],which we now describe.Call a non-empty set P offinite(directed)paths propagating if every pathin P has infinitely many extensions in P of some common length.(A pathv0...v n is an extension of a path u0...u m if m n and v i=u i for all i m.)Equivalently,P is propagating if and only if every P∈P has an extension Q such that P contains infinitely many one-vertex extensions of Q.Note thatthe paths from left to right in a bundle graph and the paths from left to rightand down in a fan graph form propagating sets:indeed,this was precisely theproperty we used in Section1to show that Adam can win the bounding gameon F and on B.The following proposition shows that the concept of a propagating set ofpaths captures precisely the structural properties of a graph that enable Adamto win the bounding game—again,independently of the choice of the graph’slabelling.Proposition3.Adam has a winning strategy for the bounding game on G ifand only if G contains a propagating set of paths.Proof.We have seen that Adam has a winning strategy if G contains apropagating set of paths.So,for the converse,suppose Adam has a winningstrategyαfor the bounding game on G.We claim that the collection of playsa1,...,a k in which Adam followsαdefines a propagating set of paths.Indeed,suppose to the contrary that some such path a1...a k has onlyfinitely many extensions of each length n.Let Eve play a sequence forcingAdam to play a1,...,a k(remember,Adam is followingα).Then,at eachn>k,when Adam has played a1,...,a n,let Eve play a number greater thanthe maximum of thefinite set of labels of possible next moves for Adam whenhe followsα.Eve clearly wins this run of the bounding game,a contradiction.We now turn to winning strategies for Eve.Theorem4.If G contains a propagating set of paths then Adam has a winningstrategy for the bounding game on G.Otherwise,Eve has a winning strategy. Proof.We assume that G contains no propagating set of paths,and construct a winning strategy for Eve.Recall that a non-empty set P offinite paths in G is propagating iffor every P ∈P there exists an n ∈ωsuch that P containsinfinitely many extensions of P all of length n .(∗)Starting with the set P 0of all finite paths in G ,let us force property (∗)on to this set by recursively deleting any paths P that violate (∗).More precisely,let us define for each ordinal α>0a set P α,as follows.If αis a successor ordinal,α=β+1say,letP α=P β {P ∈P β|P violates (∗)for P =P β};thus,P αis obtained from P βby deleting from it any path P such that,for each n ∈ω,P βcontains only finitely many extensions of P of length n .If αis a limit ordinal,let P α= β<αP β.Choose γlarge enough that P γ+1=P γ(remember,we have defined P αfor arbitrarily large α),and set P ∗=P γ.Clearly,P =P ∗satisfies (∗).By assumption,however,G contains no propagating set of paths;therefore P ∗must be empty.We may now define a strategy for Eve as follows.Consider any position where Eve is next to move.If the vertices v 0,...,v n which Adam has played so far do not form a path (in this order),let Eve’s move be arbitrary (say 0).If they do form a path,P say,let αbe minimal such that P /∈P α;as P ∗=∅,this αcertainly exists.Moreover,αis a successor ordinal (note that α>0,because P ∈P 0),say α=β+1.Then P ∈P β,but P fails to satisfy (∗)for P =P β.In particular,P has only finitely many extensions in P βby just one vertex,and we may define as Eve’s next move the number1+max { (w )|v 0...v n w is a path in P β}.Let us now show that this is a winning strategy for Eve.Consider any run of the bounding game which Eve has played according to this strategy.Let v 0,v 1,...be the vertices chosen by Adam.If they fail to form a ray in G ,then Eve has won by definition.So suppose that v 0v 1...is a ray.Let αbe minimal such that P =v 0...v k /∈P αfor some k ∈ω.As before,α=β+1for some β,so P is in P βbut fails to satisfy (∗)for P =P β.But then the same is true for every path P =v 0...v n with n k :by the minimality of α,we have P ∈P β,and P cannot have infinitely many extensions in P βof any common length,because these would also be extensions of P .Hence,all the paths v 0...v n with n k were deleted at the same time,when P αwas formed from P β.Thus in each case,the number played by Eve as e n +1is at least one greater than the label of w =v n +1,and so Eve beats Adam in every move from the k ’th position onwards.Theorem 4presents us with an obvious question:which graphs contain a propagating set of paths?A graph G is called bounded if for every labelling :V(G)→ωof its vertices there exists anω-sequence(d n)of natural numbers which dominates all the se-quences( (v n))for rays v0v1...in G.Otherwise,the graph G is unbounded. Thus to prove from the definition of boundedness that a certain graph G is bounded is like playing the part of Eve in the bounding game,but with a handicap:a labelling of G is given to us,and we have to produce a sequence (d n)which dominates every ray in G according to this labelling;we are not allowed however(as Eve is)to let the definition of the later values of d n de-pend on the initial segments of the ray we are trying to dominate.Similarly, a proof that G is unbounded is like playing the role of Adam,but with an additional advantage:we may now choose even the beginning of our ray in the full knowledge of the sequence we are trying to elude.Confirming a long-standing conjecture of Halin,it was proved in[1]that a countable graph is bounded if and only if it contains no T Tω,no bundle graph,and no fan graph.Now,it is easy to see that any graph containing a propagating set of paths must be unbounded,and we have seen that any T Tω, bundle graph or fan graph does contain a propagating set of paths.We thus have the following classification theorem for bounded graphs.Theorem 5.[1]The following statements are equivalent for countable graphs G:(i)G is bounded;(ii)G has no subgraph isomorphic a T Tω,a bundle graph,or a fan graph; (iii)G does not contain a propagating set of paths.Putting Theorems4and5together,we obtain our desired structural char-acterization for the bounding game.Theorem6.If G has a subgraph isomorphic to a T Tω,a bundle graph or a fan graph,then Adam has a winning strategy for the bounding game on G. Otherwise,Eve has a winning strategy.Let us once more point out the fact that,as a corollary of the above char-acterization theorems,the outcome of the domination game or the bounding game does not depend on‘how fast’the labelling ‘grows’:it depends only on the structure of the graph G on which the game is played.As long as G is countable(which we have so far assumed;but cf.Section4),one can also see this directly.Indeed,the bounding and the dominating game on G with labels are then equivalent to the following game on G itself:at each move Eve chooses afinite set E n of vertices,while Adam tries to construct a ray a0a1... in such a way that a n/∈E n eventually(for the dominating game)or infinitely often(for the bounding game).4.Concluding remarksThe graphs G we considered in this paper were all countable.However,the reader may have noticed that we never make full use of the fact that the la-bellings are injective:all we actually use is that every vertex of infinite degree has an infinite set of neighbours with distinct labels.With this version of a labelling,one could extend the domination and bounding games to uncount-able graphs.Alternatively,we might leave it to Adam to choose a labelling before Eve makes herfirst move.It is not difficult to show that these two generalizations are in fact equivalent.With these adaptations,all our results extend to uncountable graphs.The-orems2and4remain true,because the countability of G is not used in their proofs.Theorem6remains true,because the equivalence of(ii)and(iii)in Theorem5still holds in the uncountable case:note that any graph with a propagating set of paths must contain a countable such graph.We remark,however,that the equivalence of(i)and(ii)in Theorem5does not extend to uncountable graphs.A simple example of an unbounded graph not containing a T Tω,a bundle graph or a fan graph is the disjoint union of2ωrays.In[1],it is proved(assuming CH)that a graph is bounded if and only if it does not contain a T Tω,a bundle graph,a fan graph or the disjoint union of2ωrays.Finally,let us remark that there is also a notion of a dominating graph: G is called dominating if there exists a labelling :V(G)→ωof its vertices such that everyω-sequence of integers is dominated by the labelling along some ray in G.Viewed from the perspective of our games,the dominating graphs dif-fer from the bounded graphs in an interesting way:the structural distinction between the graphs that are dominating and those that are not does not run parallel,even in the countable case,to the distinction between those graphs on which Adam wins the dominating game and those where Eve wins.Thus,the dominating graphs are not merely those that contain a Tω:in the countable case,a graph is dominating if and only if it contains a uniform subdivision of Tω(one where at each branch vertex the incident edges are subdivided a bounded number of times),while in the uncountable case there is a similar (yet surprisingly different)characterization.The interested reader is referred to[2],where the dominating graphs are classified.Acknowledgement.We thank the referee for several thoughtful comments and suggestions.References[[1]]R.Diestel and I.Leader,A proof of the bounded graph conjecture,Invent.math.108 (1992),131–162.[[2]]R.Diestel,J.Steprans and S.Shelah,Characterizing dominating graphs,J.London Math.Soc.(to appear).[[3]]D.A.Martin,Borel determinacy,Ann.of Math.102(1975),363–371.[[4]]P.Wolfe,The strict determinateness of certain infinite games,Pac.J.Math.5(1955), 841–847.Reinhard Diestel Faculty of Mathematics Bielefeld UniversityD-33501Bielefeld Germany Imre LeaderDepartment of Pure Mathematics 16Mill LaneCambridge CB21SBEngland。