Canonical multipath-doppler coordinates in wireless communications
基于多尺度空间滤波结合两级l_1范数最近邻分类的乳腺微钙化图像病变类型诊断系统
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快速点特征直方图(FPFH)三维配准-化工大学毕业设计(外文翻译)
快速点特征直方图(FPFH)三维配准Radu Bogdan Rusu, Nico Blodow, Michael BeetzIntelligent Autonomous Systems, Technische Universit¨at M¨unchen信计1001 鄂求实2010016363摘要:在我们最近的工作[1],[2],我们提出具有稳定的多维度特征点特征直方图(PFH),它描述了三维点云数据集的一个点p周围的局部几何特征。
在本文中,我们修改他们的数学表达式并对重叠点云的三维配准问题的稳定性和复杂性进行了严格的分析。
更具体地说,我们提出几个优化方法,由任意快取以前计算的值,或通过修改他们的理论公式大大减少计算时间。
在一个新的类型,后者的结果局部特征,称为快速点特征直方图(FPFH)它保留了大部分PFH的辨别力。
此外,我们提出了为实时应用FPFH功能的一个算法的在线计算。
为了验证我们结果,我们展示他们三维配准的效率,并提出了一种新的以样本为基础共识的方法,使两个数据集到局部非线性的收敛域优化:SAC-IA(抽样一致初始对准)。
1. 引言在本文中,我们解决的各种重叠的三维点云数据视图一致对准,形成一个完整的模型(在一个刚性的意义上)的问题,也称为三维配准。
解决的办法可以将他转化成一个优化问题,即,在适当的度量空间中,通过求解最佳旋转而转换(6度)使这样的数据集之间的重叠区域之间的距离是最小的。
在空间初始未知和重叠未知的情况下,这个问题就更加困难和寻找最佳解决方案的最优化技术更容易失败。
这是因为函数优化是多维的,局部最优解决方案可能接近全局。
三维刚性配准方法的简单分类可以基于底层的优化类型,方法:全局或局部。
在第一类中也是最广为人知的都是基于全局随机采用遗传算法优化[3]或进化技术[4],其主要缺点是实际计算时间。
很多在三维配准完成的工作其实属于第二类,至今最流行配准方法无疑是在最近点迭代(ICP)算法[5],[6]。
信息与计算科学专业英语作业
大连海洋大学信息与计算科学专业英语作业指导教师:董云影学院:理学院班级:信息11-1班姓名:潘祥友学号:1107110122模糊C-均值的基础上最近的邻居间隔不完整数据的聚类算法李丹,红谷,李咏张电子与信息工程学院,大连理工大学,大连116024,中国关键词:聚类模糊C-均值数据不完整最近邻的间隔部分缺失数据集的聚类分析中的一个普遍问题。
在本文中,缺少的属性表示为间隔,和基于最近邻的时间间隔不完整的数据的一种新的模糊C均值聚类算法。
该算法估计的最近邻的区间表示缺少的属性使用的数据的属性分布信息集充分,可提高鲁棒性属性缺失的归责原则与其他数值插补方法的比较。
同时,利用区间原型形成凸超多面体可缺少的属性的不确定性,同时也反映了集群的形状在某种程度上,这是在提高聚类分析的鲁棒性很有帮助。
在UCI数据集上的实验结果的比较和分析,证明了该算法的性能。
1。
景区简介模糊C-均值(FCM)算法(Bezdek,1981)是一个有用的工具,用于聚类,将真正的S 维数据集X¼FX1N;X2;……;中古蒙古语RS分成几个集群内描述数据的底层结构,已被广泛应用于模式识别和数据挖掘。
然而,在模式分类中的应用,许多数据集不完整,即数据集可以包含向量X,缺少一个或多个属性值,作为一个结果,数据采集,故障的测量误差,缺失值,随机噪声,等和FCM是不能直接适用于这样的不完整的数据集。
在不完全数据做模式识别问题可以追溯到20世纪60年代,当塞巴斯蒂(1962)介绍了一种基于概率假设的方法。
随后,期望最大(EM)算法(Dempster,Laird,& Rubin,1977)是用来处理不完整的数据和概率聚类(克劳克兰和贝斯福德,1988)。
1998,提出了几种方法处理缺失值在FCM(宫本,高田,与umayahara,1998)。
一个基本的战略,归责,代替缺失值由相应的属性的加权平均数。
另一种方法,丢弃/忽视,忽略缺失值和计算的距离从剩余的坐标。
origin菜单栏的中文解释
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canonical polyadic 正则多元分解
canonical polyadic 正则多元分解【标题】:Canonical Polyadic 正则多元分解:揭开高维数据分析的神秘面纱【导言】在当今信息爆炸的时代里,我们面对着越来越庞大、多样化的数据集。
为了从这些海量数据中提取有价值的信息,数学家们开发了许多强大的数据分析方法。
其中,一种备受瞩目的方法是Canonical Polyadic (CP) 正则多元分解。
它是一种在高维数据集中挖掘潜在结构的有效方式,为我们揭开了高维数据分析的神秘面纱。
【深入探究高维数据分析的挑战】我们身处一个高维的世界。
然而,与传统的低维数据不同,高维数据集面临着许多挑战。
高维数据往往很稀疏,传统的统计方法可能无法充分利用数据中存在的信息。
高维数据集通常存在着大量的冗余信息,这使得数据分析变得复杂而困难。
高维数据的可解释性和可视化也是一个挑战,我们需要有效的方法来提取数据的本质特征。
【CP正则多元分解的基本概念】在面对高维数据分析的挑战时,CP正则多元分解应运而生。
它是一种基于线性代数的模型,旨在将高维数据集分解为一组低维的张量(tensor)分量。
具体而言,CP分解将一个张量表示为一系列矩阵的外积,每个矩阵代表了数据在一个模态(mode)上的特征信息。
通过这种方式,CP分解可以帮助我们发现隐藏在高维数据中的潜在结构。
【CP分解的数学形式和求解方法】CP正则多元分解的数学形式如下:\[ \mathcal{X} = \sum_{r=1}^{R} \lambda_r \mathbf{a}_r \circ\mathbf{b}_r \circ \mathbf{c}_r \]其中,\(\mathcal{X}\) 是待分解的张量,\(\lambda_r\) 是第 \(r\) 个分量的权重,\(\mathbf{a}_r, \mathbf{b}_r, \mathbf{c}_r\) 是对应的模态特征向量。
通过最小化分解的误差函数,我们可以使用不同的优化方法来求解CP分解。
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多轴差分吸收光谱法英文
多轴差分吸收光谱法英文Multi-axis differential absorption spectroscopy (MAD) is a technique used to measure the absorption of light by a sample at different angles and wavelengths. This method provides detailed information about the molecular structure and composition of the sample, making it a valuable tool in various fields such as environmental monitoring, atmospheric science, and materials analysis.In MAD, multiple light beams are directed at the sample from different angles, and the absorption of light at each angle and wavelength is measured. By analyzing the changes in absorption as a function of angle and wavelength, researchers can obtain a wealth of information about the sample, including the concentration of different molecules, their orientation, and their interactions with other substances.One of the key advantages of MAD is its ability to provide spatially resolved information about the sample. By measuring absorption at different angles, researchers can obtain a 3D map of the sample's molecular composition, allowing them to identify different components and theirspatial distribution. This makes MAD particularly usefulfor studying complex mixtures or heterogeneous samples.Another important feature of MAD is its high sensitivity. By measuring absorption at multiple angles and wavelengths, researchers can enhance the signal-to-noise ratio anddetect subtle changes in the sample's composition. This makes MAD suitable for studying trace components or low-concentration substances, which may be challenging todetect using traditional spectroscopic techniques.Furthermore, MAD can be used to study dynamic processesin real time. By continuously measuring absorption at multiple angles and wavelengths, researchers can track changes in the sample's composition as a function of time, providing valuable insights into reaction kinetics,diffusion processes, and other dynamic phenomena.In summary, multi-axis differential absorption spectroscopy is a powerful technique for studying the molecular composition and structure of samples. Its ability to provide spatially resolved, sensitive, and real-time information makes it a valuable tool for a wide range ofapplications, from environmental monitoring to materials analysis.多轴差分吸收光谱法(MAD)是一种用于测量样品在不同角度和波长下光吸收的技术。
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Common Mode Filter Design Guide
Common M ode F ilter D esign G uideIntroductionThe selection of component values for common mode filters need not be a difficult and confusing process. The use of standard filter alignments can be utilized to achieve a relatively simple and straightforward design process, though such alignments may readily be modified to utilize pre-defined component values.GeneralLine filters prevent excessive noise from being conducted between electronic equipment and the AC line; generally, the emphasis is on protecting the AC line. Figure 1 shows the use of a common mode filter between the AC line (via impedance matching circuitry) and a (noisy) power con-verter. The direction of common mode noise (noise on both lines occurring simultaneously referred to earth ground) is from the load and into the filter, where the noise common to both lines becomes sufficiently attenuated. The result-ing common mode output of the filter onto the AC line (via impedance matching circuitry) is then negligible.Figure 1.Generalized line filteringThe design of a common mode filter is essentially the design of two identical differential filters, one for each of the two polarity lines with the inductors of each side coupled by a single core:L2Figure 2.The common mode inductorFor a differential input current ( (A) to (B) through L1 and (B) to (A) through L2), the net magnetic flux which is coupled between the two inductors is zero.Any inductance encountered by the differential signal is then the result of imperfect coupling of the two chokes; they perform as independent components with their leak-age inductances responding to the differential signal: the leakage inductances attenuate the differential signal. When the inductors, L1 and L2, encounter an identical signal of the same polarity referred to ground (common mode signal), they each contribute a net, non-zero flux in the shared core; the inductors thus perform as indepen-dent components with their mutual inductance respond-ing to the common signal: the mutual inductance then attenuates this common signal.The First Order FilterThe simplest and least expensive filter to design is a first order filter; this type of filter uses a single reactive component to store certain bands of a spectral energy without passing this energy to the load. In the case of a low pass common mode filter, a common mode choke is the reactive element employed.The value of inductance required of the choke is simply the load in Ohms divided by the radian frequency at and above which the signal is to be attenuated. For example, attenu-ation at and above 4000 Hz into a 50⏲ load would require a 1.99 mH (50/(2π x 4000)) inductor. The resulting common mode filter configuration would be as follows:50Ω1.99 mHFigure 3.A first order (single pole) common mode filter The attenuation at 4000 Hz would be 3 dB, increasing at 6 dB per octave. Because of the predominant inductor dependence of a first order filter, the variations of actual choke inductance must be considered. For example, a ±20% variation of rated inductance means that the nominal 3 dB frequency of 4000 Hz could actually be anywhere in the range from 3332 Hz to 4999 Hz. It is typical for the inductance value of a common mode choketo be specified as a minimum requirement, thus insuring that the crossover frequency not be shifted too high.However, some care should be observed in choosing a choke for a first order low pass filter because a much higher than typical or minimum value of inductance may limit the choke’s useful band of attenuation.Second Order FiltersA second order filter uses two reactive components and has two advantages over the first order filter: 1) ideally, a second order filter provides 12 dB per octave attenuation (four times that of a first order filter) after the cutoff point,and 2) it provides greater attenuation at frequencies above inductor self-resonance (See Figure 4).One of the critical factors involved in the operation of higher order filters is the attenuating character at the corner frequency. Assuming tight coupling of the filter components and reasonable coupling of the choke itself (conditions we would expect to achieve), the gain near the cutoff point may be very large (several dB); moreover, the time response would be slow and oscillatory. On the other hand, the gain at the crossover point may also be less than the presumed -3 dB (3 dB attenuation), providing a good transient response, but frequency response near and below the corner frequency could be less than optimally flat.In the design of a second order filter, the damping factor (usually signified by the Greek letter zeta (ζ )) describes both the gain at the corner frequency and the time response of the filter. Figure (5) shows normalized plots of the gain versus frequency for various values of zeta.Figure 4.Analysis of a second order (two pole) common modelow pass filterThe design of a second order filter requires more care and analysis than a first order filter to obtain a suitable response near the cutoff point, but there is less concern needed at higher frequencies as previously mentioned.A ≡ ζ = 0.1;B ≡ ζ = 0.5;C ≡ ζ = 0.707;D ≡ ζ = 1.0;E ≡ ζ = 4.0Figure 5.Second order frequency response for variousdamping f actors (ζ)As the damping factor becomes smaller, the gain at the corner frequency becomes larger; the ideal limit for zero damping would be infinite gain. The inherent parasitics of real components reduce the gain expected from ideal components, but tailoring the frequency response within the few octaves of critical cutoff point is still effectively a function of ideal filter parameters (i.e., frequency, capaci-tance, inductance, resistance).L0.1W n1W n 10W nRadian Frequency,WG a i n (d B )V s V s LR s LCs LC j L R j LC LR LCCMout CMin L L n n n L ()()=++=−+⎛⎝⎜⎞⎠⎟=+−⎛⎝⎜⎞⎠⎟≡≡≡≡111111212222ωωζωωωωωωζradian frequencyR the noise load resistance LFor some types of filters, the design and damping char-acteristics may need to be maintained to meet specific performance requirements. For many actual line filters,however, a damping factor of approximately 1 or greater and a cutoff frequency within about an octave of the calculated ideal should provide suitable filtering.The following is an example of a second order low pass filter design:1)Identify the required cutoff frequency:For this example, suppose we have a switching power supply (for use in equipment covered by UL478) that is actually 24 dB noisier at 60 KH z than permissible for the intended application. For a second order filter (12dB/octave roll off) the desired corner frequency would be 15 KHz.2)Identify the load resistance at the cutoff frequency:Assume R L = 50 Ω3)Choose the desired damping factor:Choose a minimum of 0.707 which will provide 3 dB attenuation at the corner frequency while providing favorable control over filter ringing.4)Calculate required component values:Note:Damping factors much greater than 1 may causeunacceptably high attenuation of lower frequen-cies whereas a damping factor much less than 0.707 may cause undesired ringing and the filter may itself produce noise.Third Order FiltersA third order filter ideally yields an attenuation of 18 dB per octave above the cutoff point (or cutoff points if the three corner frequencies are not simultaneous); this is the prominently positive aspect of this higher order filter. The primary disadvantage is cost since three reactive compo-nents are now required. H igher than third order filters are generally cost-prohibitive.Figure 6.Analysis of a third order (three pole) low pass filter where ω1, ω2 and ω4 occur at the same -3dB frequency of ω05)Choose available components:C = 0.05 µF (Largest standard capacitor value that will meet leakage current requirements for UL478/CSA C22.2 No. 1: a 300% decrease from design)L = 2.1 mH (Approx. 300% larger than design to compensate for reduction or capacitance: Coilcraft standard part #E3493-A)6)Calculate actual frequency, damping factor, and at-tenuation for components chosen:ζ = 2.05 (a damping factor of about 1 or more is acceptible)Attenuation = (12 dB/octave) x 2 octaves = 24 dB 7)The resulting filter is that of figure (4) with:L = 2.1 mH; C = 0.05 µF; R L = 50 ΩL 1L 2VCMout s VCMin s R R L s R L s sC R L s sC R L s L L s L s sC L L R s L Cs L L C R s L L L L L L L()()()()=+⎛⎝⎜⎞⎠⎟+++++⎛⎝⎜⎜⎜⎜⎞⎠⎟⎟⎟⎟=++++222121*********11Butterworth →+++112212233s s s n n n ωωω()()L L R R L L L n n L 12111222+==+ωω;()L L C n 1n2C =2;ωω2211414=.L L L L n n n 12L n3n2L2n2L2C R =1;R R ωωωωωω33224422===ωπωζωμn n n Lf C L L R L =====294248070727502rad /sec =1Hn .1215532πLC=Hz (very nearly 15KHz)The design of a generic filter is readily accomplished by using standard alignments such as the Butterworth (“maxi-mally flat”) alignments. Figure (6) shows the general analysis and component relationships to the Butterworth alignments for a third order low pass filter. Butterworth alignments provide an inherent ζ of 0.707 and a -3 dB point at the crossover frequency. The Butterworth alignments for the first three orders of low pass filters are shown in Figure (7).The design of a line filter need not obey the Butterworth alignments precisely (although such alignments do pro-vide a good basis for design); moreover, because of leakage current limits placed upon electronic equipment (thus limiting the amount of filter capacitance to ground),adjustments to the alignments are usually required, but they can be executed very simply as follows:1)First design a second order low pass with ζ ≥ 0.52)Add a third pole (which has the desired corner fre-quency) by cascading a second inductor between the second order filter and the noise load:L = R/ (2 π f c )Where f c is the desired corner frequency.Design ProcedureThe following example determines the required compo-nent values for a third order filter (for the same require-ments as the previous second order design example).1)List the desired crossover frequency, load resistance:Choose f c = 15000 Hz Choose R L = 50 Ω2)Design a second order filter with ζ = 0.5 (see second order example above):3)Design the third pole:R L /(2πf c ) = L 250/(2π15000) = 0.531 mH4)Choose available components and check the resulting cutoff frequency and attenuation:L2 = 0.508 mH (Coilcraft #E3506-A)f n= R/(2πL 1 )= 15665 HzAttenuation at 60 KHZ: 24 dB (second order filter) +2.9 octave × 6 = 41.4 dB5)The resulting filter configuration is that of figure (6)with:L 1 = 2.1 mH L 2 = 0.508 mH R L = 50 ΩConclusionsSpecific filter alignments may be calculated by manipu-lating the transfer function coefficients (component val-ues) of a filter to achieve a specific damping factor.A step-by-step design procedure may utilize standard filter alignments, eliminating the need to calculate the damping factor directly for critical filtering. Line filters,with their unique requirements, yet non-critical character-istics, are easily designed using a minimum allowable damping factor.Standard filter alignments assume ideal filter compo-nents; this does not necessarily hold true, especially at higher frequencies. For a discussion of the non-ideal character of common mode filter inductors refer to the application note “Common Mode Filter Inductor Analysis,”available from Coilcraft.Figure 7.The first three order low pass filters and their Butterworth alignmentse i +–e O +–R LL 2Ce i +–e O +–R LL 1Ce i +–e O +–R LL 1L 2Filter SchematicFilter Transfer FunctionButterworthAlignmentFirst OrderSecond OrderThird Ordere e Ls R o iL =+11e e LCs Ls R oi L=++112e e L L R s L Cs L L s R o iLL =++++111231212()e e s o in=+11ωe e LCs Ls R oiL =++112e e s s so i n n n =+++122133221ωωω。
CODEV10.2说明书3
Application Programming InterfaceReference GuideVersion 10.2December 2009Pasadena, California 91107Phone: (626) 795-9101Fax: (626) 795-0184E-mail: service@The information in this document is subject to change without notice and should not be construed as a commitment by Optical Research Associates (ORA®). ORA assumes no liability for any errors that may Arrayappear in this document.The software described in this document is furnished under license and may be used or copied only in accordance with the terms of such license. The CODE V output shown (plotted and printed) may vary in different versions.Copyright © 2009 by Optical Research Associates. All rights reserved.Proprietary Software NotificationCODE V® is the proprietary and confidential property of ORA and/or its suppliers. It is licensed for use on the designated equipment on which it was originally installed and cannot be modified, duplicated, or copied in any form without prior written consent of ORA. If supplied under a U.S. Government contract the following also applies:Restricted Rights LegendUse, duplication, or disclosure by the Government is subject to restrictions as set forth in subparagraph (c)(1)(ii) of the Rights in Technical Data and Computer Software clause at DFARS 252.227-7013 or insubparagraph (c) of the Commercial Computer Software - Restricted Rights clause at FARS 52.227-19.ORA, CODE V, and LightTools are registered trademarks of Optical Research Associates. Other trademarksor marks are the property of their respective companies.CODE V API Reference Guide Contents • iiiContentsChapter 1OverviewWhat is the CODE V API? (1)Requirements (1)A Note about the DEFAULTS.SEQ File (2)Getting Started (2)DisplayAlerts Property (4)Speeding Up COM Client Execution...............................................................................................4Chapter 2CODE V Interface FunctionsGeneral Utility Functions (6)Start/StopCodeV (6)Get/SetCommandTimeout (7)Get/SetMaxTextBufferSize (8)Get/SetStartingDirectory (9)GetCodeVVersion (10)Asynchronous Usage Functions (11)AsyncCommand (11)IsExecutingCommand (12)Wait (13)GetCommandOutput (14)StopCommand (15)Synchronous Usage Functions (16)Command (16)EvaluateExpression (17)CODE V State Information (18)GetCurrentOption (18)GetCurrentSubOption (19)GetZoomCount (20)GetSurfaceCount (21)GetFieldCount (22)GetWavelengthCount (23)GetDimension (24)GetStopSurface (25)GetMaxAperture (26)Math and Optical MACRO Functions (27)BESTSPH (27)EVALZERN (28)FITERROR (29)GAUSSBEAM (30)GAUSSWTS (32)INDEX (33)MTF_1FLD (34)NORMRADIUS (35)POLGRID (36)RAYPOL (39)RAYRSI (42)RAYSIN..................................................................................................................................43iv • Contents CODE V API Reference GuideRAYTRA................................................................................................................................44RMSWE..................................................................................................................................45RMS_1FLD.............................................................................................................................48SAGF (50)SASF (51)SURFSAGD (52)SVD (53)TRA_1FLD (54)TRANSFORM (56)ZERNIKE (57)ZERNIKEGQ (59)Zernike Fitting Functions (61)ZFRCOEF (62)Buffer Functions (63)Sample Code: Outputting buffer data from CODE V (63)BufferToArray (64)ArrayToBuffer (65)Chapter 3CODE V API by ExampleWriting PSF Data to an Excel Spreadsheet (67)Results (69)Creating a Surface Listing (70)MATLAB Sample File...................................................................................................................72Appendix A CVCommand ErrorsE_INVALIDARG (73)DISP_E_BADINDEX (73)E_UNEXPECTED (73)FACILITY_ITF..............................................................................................................................73Chapter 1OverviewWhat is the CODE V API?The CODE V API is an application programming interface designed to allow access from otherprograms to CODE V commands. The CODE V API uses the Microsoft Windows standardComponent Object Model (COM) interface1. This enables you to execute CODE V commandsusing applications such as Microsoft Visual Basic (VB), Microsoft Office Applications, C++,MATLAB, or any other application that supports Windows COM architecture. The CODE V API is particularly useful for automating tasks or retrieving data used in calculations in other programs.Both Visual Basic and Excel provide an integrated development environment in which you candevelop CODE V command functions.2 This type of environment provides context-sensitiveediting and debugging, Windows standard forms, object oriented programming capabilities(Classes), standard functions in Visual Basic/Excel (or the client program), external object libraries known as dynamic link libraries (DLLs), as well as other conveniences that can enhance thefunction writing process.The CODE V API has no graphical user interface, and therefore no graphics support; any plotscreated with a CODE V API function must be output to a file or they are lost. Plot files can beviewed either in CODE V, or in the standalone CODE V Viewer program (CVPlotView). RequirementsIn order to use the CODE V API to write and run commands, you must have installed:•CODE V 9.30 or laterDuring installation, CODE V is configured to support API command execution. This processregisters CODE V as a COM server on your system (cvcommand).•Any Visual Basic compliant application (such as Microsoft Excel, Word, PowerPoint, Visual Basic, or MATLAB) or any other Windows program that supports Microsoft COMarchitecture1. The COM enables Windows Programs to communicate with each other using the Client/Serverconcept. For example, the program that initiates the communication process is referred to asthe client, and the program that responds to client’s requests is referred to as the server. Currently,CODE V can only act as a server, meaning that it can only respond to client programs.2. This document concentrates on Visual Basic as the client for writing functions. To use other pro-grams, please refer to their documentation (under “Automation” or “COM” support).CODE V API Reference Guide Overview • 12 • Overview CODE V API Reference GuideA Note about the DEFAULTS.SEQ FileWhen you use the CODE V API, note that your DEFAULTS.SEQ file is not automatically loaded when CODE V is run. You must include the following command in your function to load this file:mand("in defaults.seq")Getting StartedThis example describes how to write a very simple command function using the Visual Basic Editor provided with Microsoft Excel.1.Start Microsoft Excel.2.Select Tools > Macro > Visual Basic Editor .The Microsoft VisualBasic window is displayed.3.Add the CODE V Command Type Library as a reference by doing the following:a.Select Tools > References . . ..b.In the References - VBAProject window, select the Optical Research AssociatesCVCommand Type Library and click OK .If you are running Excel 97, the CVCommand Type Library may not be listed in theAvailable References. If it is not, select Browse and navigate to the CODE V installation directory. Click on cvcommand.tlb and click Open to add the CVCommand Type Library to the Available References.3.Back in the Microsoft Visual Basic window, select Tools > Macros .4.In the Macros window, key in a name and click Create .5.In the Book1 - Module1(Code) window, you can begin writing your macro.a.Declare the session variable:Dim Session As CVCommand b.Request an instance of the CVCommand interface using the Set statement:Set session = CreateObject("mand.930")This instance should be requested by object name, which in this case is version 9.30 ofCODE V . A specific version number should be requested because the interfaces maychange with later versions of CODE V.CODE V API Reference Guide Overview • 3c.Once an instance is created, the CODE V utility functions can be called on to set up theenvironment parameters, such as buffer size and starting directory. For example:session.SetStartingDirectory("c:\CVUSER")e the StartCodeV function to start up CODE V:session.StartCodeVplete the macro as desired and save your project.Following is a sample macro that starts CODE V , opens the sample lens file dbgauss.len, and optimizes the lens:Sub RunCodeV()Dim Session As CVCommand'Create an instance of CODE V and set the starting directory to c:\CVUSER Set session = CreateObject("mand.xxx")'where xxx is the CODE V version; for example, xxx=101 for version 10.1 session.SetStartingDirectory("c:\CVUSER")session.StartCodeVmand("in defaults.seq")'load a lens (dbgauss) and run AUTO to optimize itresult = mand("res cv_lens:dbgauss")result = mand("aut; go")MsgBox (result)'evaluate the Effective Focal Lengthresult = session.EvaluateExpression ("(efl)")'Shut down the instance of CODE Vsession.StopCodeVSet session = NothingEnd Sub6.From the Visual Basic window, click Run > Run Sub/User Form , or click the Run icon on thetoolbar.The macro will run CODE V and execute the specified CODE V command functions.For details about the available CODE V commands available for use with the CODE V API, go to Chapter 2, “CODE V Interface Functions” on page5.DisplayAlerts PropertyIf your macro starts a CODE V process that takes time, and waits for a response, then VB or VBA Array will try to issue a warning message indicating that the server is not responding and may not run the remaining portion of the macro. To suppress this message, you can use the following code:in VBA:Application.DisplayAlerts = Falsedisables the display of alert boxes; however, this setting should be used selectively and changedback to True when not needed.in VB, you can set:App.OleRequestPendingTimeout = NApp.OleRequestBusyTimeout = Nwhere N is the number of milliseconds. N should be greater than the time it takes to run the process. Speeding Up COM Client ExecutionThe REC command allows you to disable recording of data in the CODE V recovery file, whichcan help speed up execution of COM clients. See “Defining Configuration - I/O” on page24-19 ofthe CODE V Reference Manual for details about REC. Note that, by default, CODE V alwaysrecords data in the recovery file, which is recommended for general CODE V usage.4 • Overview CODE V API Reference GuideCODE V API Reference Guide CODE V Interface Functions • 5Chapter 2CODE V Interface FunctionsThis section contains details for each CODE V interface function. The CODE V interface functions are grouped in the following categories, based on what they do.•General Utility Functions.................................................................................... 6•Asynchronous Usage Functions......................................................................... 11•Synchronous Usage Functions........................................................................... 16•CODE V State Information ............................................................................... 18•Math and Optical MACRO Functions............................................................... 27•Buffer Functions................................................................................................63General Utility FunctionsStart/StopCodeVThese functions start or stop the CODE V session being run by CVCommand. Start must be called before any function other than Set/GetCommandTimeout, Set/GetMaxTextBufferSize,GetCodeVVersion, or Set/GetStartingDirectory is called. StopCodeV must be called when you are done running the session of CODE V.Visual Basic SyntaxStartCodeV()StopCodeV()6 • CODE V Interface Functions CODE V API Reference GuideGet/SetCommandTimeoutThese functions are used to get or set the timeout for synchronous commands. They have no effect on asynchronous commands.Visual Basic SyntaxSetCommandTimeout(nTimeout As Integer)GetCommandTimeout() As IntegerParameterReturn ValueFor GetCommandTimeout, the current timeout time in seconds.nTimeoutCurrent timeout time in secondsGet/SetMaxTextBufferSizeThese functions are used to get or set the maximum buffer size for text returned by the Command and GetCommandOutput functions.Visual Basic SyntaxSetMaxTextBufferSize(lSize As Long)GetMaxTextBufferSize() As LongParameterReturn ValueFor GetMaxTextBufferSize, a pointer to a long integer that contains the current maximum buffer size.lSize Long integer containing the desired maximum buffer size in characters.Default is 256000.Get/SetStartingDirectoryGet or set the working directory for CODE V . SetStartingDirectory must be called before StartCodeV to set the directory of execution.Visual Basic SyntaxGetStartingDirectory() As StringSetStartingDirectory(bstrStartingDirectory As String)ParameterReturn ValuePointer to a string defining the current starting directory.bstrStartingDirectoryString defining the desired starting directory.GetCodeVVersionVisual Basic SyntaxGetCodeVVersion() As StringParameterNone.Return ValueVersion of CODE V that is running.Asynchronous Usage FunctionsAsyncCommandStart an asynchronous command. Only one AsyncCommand call can be run at a time, but multiple AsyncCommand calls can be made during a CVCommand session. This function call fails if CODE V is already running a command. Calling this function clears the results of the previous asynchronous function call.Visual Basic SyntaxAsyncCommand(bstrCommandLine As String)ParameterbstrCommandLineCommand to be executed.IsExecutingCommandVisual Basic SyntaxIsExecutingCommand() As LongParameterNone.Return ValueBoolean that indicates whether or not an asynchronous command is currently executing.WaitWait for an asynchronous command to complete.Visual Basic SyntaxWait(nWaitTime As Integer) As CVWaitStatusParameterReturn ValueEnumeration for wait status, either Completed or TimeOut:Completed Command completed 1TimeOut Wait timed out with the command still runningnWaitTimeTime to wait in seconds.GetCommandOutputEvaluateExpression, or math and optical functions) between calls to AsyncCommand andGetCommandOutput. This will preserve the buffer between those two calls.Visual Basic SyntaxGetCommandOutput() As StringParameterNone.Return ValueString containing the output. Its maximum length is the maximum buffer size.StopCommandThis function aborts the currently running CODE V calculation.Visual Basic SyntaxStopCommand()Synchronous Usage FunctionsCommandThis function sends a command to the CODE V session being run by CVCommand and returns its output. Calling this function clears the results of the previous asynchronous function call.Visual Basic SyntaxCommand(bstrCommandLine As String) As StringParameterReturn ValueThe command output. Its size is limited by the maximum buffer size set withSetMaxTextBufferSize.bstrCommandLineCODE V command.EvaluateExpressionThis function evaluates an expression and returns its value. It is equivalent to the EV A command in CODE V .Visual Basic SyntaxEvaluateExpression(bstrExpression As String) As StringParameterReturn ValuePointer to a string into which CVCommand will put the results of the evaluation. Note that because this is a string, the value is only as precise as the output into the string; it is not a true floating point value.bstrExpressionString containing the expression to evaluate.CODE V State Informationasynchronous command.GetCurrentOptionReturns the name of the current option.Visual Basic SyntaxGetCurrentOption() As StringParameterNone.Return ValueThe option short name (e.g., AUT for Automatic Design). Returns "CHA" if CODE V is notcurrently in an option.GetCurrentSubOptionVisual Basic SyntaxGetCurrentSubOption() As StringParameterNone.Return ValueThe option name. Returns an empty string if CODE V is not currently in a sub-option.Visual Basic SyntaxGetZoomCount() As Integer ParameterNone.Return ValueThe current number of zoom positions in the lens.Visual Basic SyntaxGetSurfaceCount() As Integer ParameterNone.Return ValueThe current number of surfaces.GetFieldCountVisual Basic SyntaxGetFieldCount() As Integer ParameterNone.Return ValueThe current number of fields.GetWavelengthCountVisual Basic SyntaxGetWavelengthCount() As Integer ParameterNone.Return ValueThe current number of wavelengths.GetDimensionReturns a value representing the type of dimensions in the system.Visual Basic SyntaxGetDimension() As IntegerParameterNone.Return ValuesThe value representing the type of dimensions in the system:0Inches1Centimeters2MillimetersVisual Basic SyntaxGetStopSurface() As Integer ParameterNone.Return ValueThe surface number of the current stop surface.Returns the maximum aperture size for the specified surface and zoom.Visual Basic SyntaxGetMaxAperture(nSurface As Integer, nZoom As Integer) As DoubleParametersReturn ValueMaximum aperture size. This uses the “MAP” database item.nSurfaceNumber of the surface for which the maximum aperture will be oomZoom position at which the maximum aperture will be determined.Math and Optical MACRO FunctionsThe following functions are equivalent to calling various CODE V macro functions. For more details about the CODE V macro functions referenced, see “Language Reference” on page 25A-1 of the CODE V Reference Manual .BESTSPHThis is equivalent to calling the BESTSPH macro function in CODE V .Visual Basic SyntaxBESTSPH(nSurface As Integer, nZoomPos As Integer,dblMinHeight As Double, dblMaxHeight As Double) As DoubleParametersReturn ValueThe return value of the BESTSPH macro function. It is the curvature of the best fitting sphere.nSurface Desired surface.nZoomPos Desired zoom position.dblMinHeight Minimum Y coordinate.dblMaxHeightMaximum Y coordinate.EVALZERNThis is equivalent to calling the EV ALZERN macro function in CODE V . The EV ALZERN macron function evaluates a Zernike polynomial generated with the ZERNIKE, ZERNIKEGQ, orZFRCOEF macro function and computes the value of the polynomial at a point X,Y , where X and Y are normalized to the unit circle.Visual Basic SyntaxEVALZERN(nWavelengthNum As Integer, nFieldNum As Integer, nZoomPos As Integer, dblX As Double, dblY As Double, nPolType As Integer, eOutputType As CVZernOutputTypeEnum, eZernType As CVZernTypeEnum) As DoubleParametersReturn ValueThe value of the Zernike polynomial at the specified coordinate. If the polynomial has not been defined with the ZERNIKE, ZERNIKEGQ, or ZFRCOEF function, EV ALZERN returns a value of -1e10.nWavelengthNum Number of the wavelength defined in ZERNIKE, ZERNIKEGQ, or ZFRCOEF.nFieldNum Number of the field point defined in ZERNIKE, ZERNIKEGQ, or ZFRCOEF.nZoomPos Zoom position defined in ZERNIKE, ZERNIKEGQ, or ZFRCOEF.dblX X coordinate to be evaluated.dblY Y coordinate to be evaluated.nPolTypeNumber specifying whether polarization ray tracing is enabled for this computation; matches the number defined in ZERNIKE or ZERNIKEGQ. If you used ZFRCOEF, this must be 0.eOutputTypeEnumeration of the output type ('intensity' or 'phase'), specifying intensity or phase. Matches the type used in ZERNIKE or ZERNI-KEGQ. If you used ZFRCOEF, the output must be 'phase.'eZernTypeType of the Zernike polynomial. Matches the expression defined inZERNIKE or ZERNIKEGQ. If you used ZFRCOEF, it must be 'zfr.'FITERRORThis is equivalent to calling the FITERROR macro function in CODE V .Visual Basic SyntaxFITERROR(nWavelengthNum As Integer, nFieldNum As Integer, nZoomPos As Integer, nPolType As Integer, eOutputType As CVZernOutputTypeEnum, eZernType As CVZernTypeEnum) As DoubleParametersReturn ValueThe RMS fit error of the Zernike polynomial. If the polynomial has not been defined with the ZERNIKE or ZFRCOEF function, FITERROR returns a value of -1. If used with the ZERNIKEGQ macro function, returns a value of 0.nWavelengthNum Number of the wavelength defined in ZERNIKE or ZFRCOEF.nFieldNum Number of the field point defined in ZERNIKE or oomPos Zoom position defined in ZERNIKE or ZFRCOEF.nPolTypeNumber specifying whether polarization ray tracing is enabled for this computation; matches the number defined in ZERNIKE. If you used ZFRCOEF, this must be 0.eOutputTypeEnumeration of the output type ('intensity' or 'phase'), specifying intensity or phase. Matches the type used in ZERNIKE. If you used ZFRCOEF, the output must be 'phase.'eZernTypeType of the Zernike polynomial. Matches the expression defined inZERNIKE. If you used ZFRCOEF, it must be 'zfr.'GAUSSBEAMThis is equivalent to calling the GAUSSBEAM macro function in CODE V .Visual Basic SyntaxGAUSSBEAM(nSurface As Integer, nZoomPos As Integer, nFieldNum As Integer, nWavelengthNum As Integer, psaInput() As Double, eOutputType As CVGaussbeamOutputTypeEnum) As DoubleParametersnSurfaceThe surface number to use. For non-sequential systems, if you enter a negative value, that value refers to the hit number rather than the sur-face number. This gives you direct access to the information by hit number.nZoomPos Zoom position to use.nFieldNumNumber of field positions to use.nWavelengthNum Number of the wavelength to use (not the value of the wavelength).psaInputA five-element input array containing the following parameters (in this order): initial beam-width radius (at the object plane) at the 1/ e 2 inten-sity point in the X meridian (WRX), initial beam-width radius (at the object plane) at the 1/ e 2 intensity point in the Y meridian (WRY), radius of curvature of input wavefront (at object plane) in X meridian (RCX), radius of curvature of input wavefront (at object plane) in Y meridian (RCY), orientation (in degrees) of input beam definition about the optical (z) axis (AZI).eOutputTypeEnumeration specifying the output value of the function:0PROP Propagation distance to the next surface 1BSDX X semi-diameter of the beam 2BSDY Y semi-diameter of the beam 3BANG Beam angle (in degrees)4WCUX X Curvature of the Wavefront 5WCUY Y Curvature of the Wavefront 6WSDX X semi-diameter of the waist 7WSDY Y semi-diameter of the waist 8WDSX X waist distance from the surface 9WDSY Y waist distance from the surface 10SURX X Coordinate of the beam on the surface 11SURY Y Coordinate of the beam on the surface 12SURZZ Coordinate of the beam on the surfaceReturn ValueFor non-sequential systems, the macro function returns results for the last time the specified surface was hit. If that surface was not hit, the function returns 0.13RDCL L Direction cosine (geo) of center of beam prior to surface14RDCM M Direction cosine (geo) of center of beam prior to surface15RDCN N Direction cosine (geo) of center of beam prior to surface16AINC Angle of incidence (in degrees) of center of beam at surface17SURNFor NS systems. Return the surface number for the hit number specified with the surface numparameterGAUSSWTSThis function is equivalent to calling the GAUSSWTS macro function in CODE V .Visual Basic SyntaxGAUSSWTS(nNumInputPts As Integer, psaInputCoords() As Double, psalInputWeights() As Double, nNumQuadPts As Integer, psaCoords() As Double, psaWeights() As Double) As DoubleParametersReturn ValueThe return value of the GAUSSWTS macro function. It is 0 if there are no errors in the computation, and -1 if any errors are encountered.nNumInputPts Number of input points at which weights are supplied.psaInputCoordsInput array of coordinates at which weights are supplied. It must be nNumInputPts long. The input coordinates do not need to be equally spaced.psalInputWeights An input array, dimensioned at nNumInputPts, of the weighting function at the points specified in psaInputCoords.nNumQuadPts Number of Gaussian quadrature points and weights desired.psaCoords An output array, dimensioned at nNumQuadPts, of the coordinates to be used for the numerical integration.psaWeightsAn output array, dimensioned at nNumQuadPts. It will receive theweights to be used for the numerical integration.INDEXThis is equivalent to calling the INDEX macro function in CODE V .Visual Basic SyntaxINDEX(nSurface As Integer, nZoomPos As Integer,nWavelengthNum As Integer, nGlassNum As Integer, dblX As Double, dblY As Double, dblZ As Double) As DoubleParametersReturn ValueThe refractive index at the specified point. Note that it can be positive or negative, depending on the direction the light is traveling. If the first four parameters are outside their allowed range or if the index cannot be computed for any reason, the return value is set to 0.0.nSurface Surface number of the GRIN oomPosZoom position.nWavelengthNum Number of the wavelength to be used (not the wavelength value).nGlassNum Glass number (for NSS surfaces). Value must be either 1 or 2. For sequential surfaces, use 1.dblX, dblY , dblZCoordinates relative to the surface origin where the index is to becomputed.MTF_1FLDMTF_1FLD computes the MTF of the lens system including or excluding diffraction effects,assuming either a sine wave or a square wave object, similar to the MTF option. It is equivalent to calling the MTF_1FLD macro function in CODE V .Visual Basic SytaxMTF_1FLD(nZoomPos As Integer, nFieldNum As Integer, Frequency As Double, Azimuth As Double, NRD As Integer, MTFValues() As Double, MTFtype As CVMTFTypeEnum, MTFWave As CVMTFWaveEnum) As DoubleParametersReturn ValueThe return value of the function is the modulation. If there is an error in the computation or inputs, the return value is -1. Since a negative modulation is not valid, any negative return value indicates that the calculation failed.nZoomPos Zoom position to use. Range: 1 to (NUM Z).nFieldNum Number of field point to use. Range: 1 to (NUM F).FrequencySpatial frequency at the image surface. Units are cycles/mm for focal systems, and cycles per angular measure for afocal (AFC) systems, where the angular measure is defined by the angular units specification (ADM).Azimuth Orientation of the spatial frequency at the image, in degrees.NRD Number of grid rays across the diameter of the pupil. If nrd is set to zero, the calculation is performed using a default value of 60.MTFValuesThe output array name must be declared before the macro is called, and is a one-dimensional output array that will contain the following six elements:1.Modulation2.Phase (degrees)3.Analytic diffraction limit value4.Actual diffraction limit value5.Illumination for unit brightness6.Number of rays traced (in convolved pupil for diffraction MTF)These data values correspond to the equivalent values output by the MTF option.MTFtype String expression specifying diffraction MTF ('DIF') or geometrical MTF ('GEO').MTFWaveString expression specifying sine wave response ('SIW') or square waveresponse ('SQW').。
计算机控制系统习题及部分解答
g0=(1/T)*5*abs(1/(10+(GW+ws)*i)); G11=[g0];
g0=(1/T)*5*abs(1/(10+(GW-ws)*i)); G12=[g0];
g0=(1/T)*5*abs(1/(10+(GW+2*ws)*i)); G21=[g0];
g0=(1/T)*5*abs(1/(10+(GW-2*ws)*i)); G22=[g0];
题图 1-6 飞机连续模拟式姿态角控制系统结构示意图
第2章 习 题
2-1 下述信号被理想采样开关采样,采样周期为 T,试写出采样信号的表达式。
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(3) f (t) = e−at sin(ωt)
解:
∞
∑ (1) f *(t) = 1(kT )δ (t − kT ) ; k =0 ∞
结果表明,不满足采样定理,高频信号将变为低频信号。
2-8
试证明
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计算。采样幅频曲线可以用如下 MATLAB 程序绘图:
T=0.1;
尺度相互作用墨西哥帽小波提取图像特征点
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文章 编 号 :0 72 8 2 1 ) 10 2 — 5 1 0 — 7 0( 0 2 0 — 1 5 0
基于多结点样条磨光函数的几何迭代法
16
专论:CAD&CG GDC 2018 桂林
2019 年
据点集用迭代的方法调整控制点,形成逐渐逼近 控制点的新样条函数,最终形成一条光滑且具有 更高逼近性的曲线或曲面的一种图形数据拟合 方法[3]。
几何迭代法在计算机辅助几何设计(computeraided geometric design,CAGD)中,解决的主要问 题是工业产品几何形状的数字描述,例如汽车车 轮、涡轮发动机、飞机外形的设计。CAGD 技术起 源于航空工业,由于飞机外形流线型的特殊结构是 由多个自由的曲线及曲面组成的,所以 CAGD 技术 的研究与曲线、曲面的发展息息相关。
条曲线插值在几何迭代中的收敛速度和迭代精度,提出了基于多结点样条磨光函数的几何迭代
法,引入多结点样条磨光函数,在曲线拟合时把多结点样条磨光方法和几何迭代方法结合,经过
磨光和迭代,在 L-BFGS 迭代算法的最优解下构造具有高逼近性的曲线拟合方法。实验结果表明,
在相同精度下,该方法不仅减少了迭代次数,且提高了迭代速度,可以用于飞机、汽车等外形设
2019 年 2 月 第 40 卷 第 1 期
图学学报
JOURNAL OF GRAPHICS
February 2019 Vol.40 No.1
基于多结点样条磨光函数的几何迭代法
霍彦妏, 蔡占川
(澳门科技大学资讯科技学院,澳门 999078)
摘
要:几何迭代法在计算机辅助几何设计(CAGD)中有广泛地应用,为了提高传统的 B-样
Geometric Iteration Method Based on Many-Knot Spline Polishing Functions
HUO Yan-Βιβλιοθήκη en, CAI Zhan-chuan
核磁共振中常用的英文缩写和中文名称
NMR 中常用的英文缩写和中文名称收集了一些NMR 中常用的英文缩写,译出其中文名称,供初学者参考,不妥之处请指出,也请继续添加.相关附件NMR 中常用的英文缩写和中文名称APT Attached Proton Test 质子连接实验ASIS Aromatic Solvent Induced Shift 芳香溶剂诱导位移BBDR Broad Band Double Resonance 宽带双共振BIRD Bilinear Rotation Decoupling 双线性旋转去偶(脉冲)COLOC Correlated Spectroscopy for Long Range Coupling 远程偶合相关谱COSY ( Homonuclear chemical shift ) COrrelation SpectroscopY (同核化学位移)相关谱CP Cross Polarization 交叉极化CP/MAS Cross Polarization / Magic Angle Spinning 交叉极化魔角自旋CSA Chemical Shift Anisotropy 化学位移各向异性CSCM Chemical Shift Correlation Map 化学位移相关图CW continuous wave 连续波DD Dipole-Dipole 偶极-偶极DECSY Double-quantum Echo Correlated Spectroscopy 双量子回波相关谱DEPT Distortionless Enhancement by Polarization Transfer 无畸变极化转移增强2DFTS two Dimensional FT Spectroscopy 二维傅立叶变换谱DNMR Dynamic NMR 动态NMRDNP Dynamic Nuclear Polarization 动态核极化DQ(C) Double Quantum (Coherence) 双量子(相干)DQD Digital Quadrature Detection 数字正交检测DQF Double Quantum Filter 双量子滤波DQF-COSY Double Quantum Filtered COSY 双量子滤波COSYDRDS Double Resonance Difference Spectroscopy 双共振差谱EXSY Exchange Spectroscopy 交换谱FFT Fast Fourier Transformation 快速傅立叶变换FID Free Induction Decay 自由诱导衰减H,C-COSY 1H,13C chemical-shift COrrelation SpectroscopY 1H,13C 化学位移相关谱H,X-COSY 1H,X-nucleus chemical-shift COrrelation SpectroscopY 1H,X- 核化学位移相关谱HETCOR Heteronuclear Correlation Spectroscopy 异核相关谱HMBC Heteronuclear Multiple-Bond Correlation 异核多键相关HMQC Heteronuclear Multiple Quantum Coherence 异核多量子相干HOESY Heteronuclear Overhauser Effect Spectroscopy 异核Overhause 效应谱HOHAHA Homonuclear Hartmann-Hahn spectroscopy 同核Hartmann-Hahn 谱HR High Resolution 高分辨HSQC Heteronuclear Single Quantum Coherence 异核单量子相干INADEQUATE Incredible Natural Abundance Double Quantum Transfer Experiment 稀核双量子转移实验(简称双量子实验,或双量子谱)INDOR Internuclear Double Resonance 核间双共振INEPT Insensitive Nuclei Enhanced by Polarization 非灵敏核极化转移增强INVERSE H,X correlation via 1H detection 检测1H 的H,X 核相关IR Inversion-Recovery 反(翻)转回复JRES J-resolved spectroscopy J-分解谱LIS Lanthanide (chemical shift reagent ) Induced Shift 镧系(化学位移试剂)诱导位移LSR Lanthanide Shift Reagent 镧系位移试剂MAS Magic-Angle Spinning 魔角自旋MQ(C)Multiple-Quantum ( Coherence )多量子(相干)MQF Multiple-Quantum Filter 多量子滤波MQMAS Multiple-Quantum Magic-Angle Spinning 多量子魔角自旋MQS Multi Quantum Spectroscopy 多量子谱NMR Nuclear Magnetic Resonance 核磁共振NOE Nuclear Overhauser Effect 核Overhauser 效应(NOE)NOESY Nuclear Overhauser Effect Spectroscopy 二维NOE 谱NQR Nuclear Quadrupole Resonance 核四极共振PFG Pulsed Gradient Field 脉冲梯度场PGSE Pulsed Gradient Spin Echo 脉冲梯度自旋回波PRFT Partially Relaxed Fourier Transform 部分弛豫傅立叶变换PSD Phase-sensitive Detection 相敏检测PW Pulse Width 脉宽RCT Relayed Coherence Transfer 接力相干转移RECSY Multistep Relayed Coherence Spectroscopy 多步接力相干谱REDOR Rotational Echo Double Resonance 旋转回波双共振RELAY Relayed Correlation Spectroscopy 接力相关谱RF Radio Frequency 射频ROESY Rotating Frame Overhauser Effect Spectroscopy 旋转坐标系NOE 谱ROTO ROESY-TOCSY Relay ROESY-TOCSY 接力谱SC Scalar Coupling 标量偶合SDDS Spin Decoupling Difference Spectroscopy 自旋去偶差谱SE Spin Echo 自旋回波SECSY Spin-Echo Correlated Spectroscopy 自旋回波相关谱SEDOR Spin Echo Double Resonance 自旋回波双共振SEFT Spin-Echo Fourier Tran sform Spectroscopy (with J modulati on)(J-调制)自旋回波傅立叶变换谱SELINCOR SELINQUATE SFORD SNR or S/NSelective Inverse Correlation 选择性反相关Selective INADEQUA TE 选择性双量子(实验)Single Frequency Off-Resonance Decoupling 单频偏共振去偶Signal-to-noise Ratio 信/ 燥比SQF Single-Quantum Filter 单量子滤波SRTCF TOCSY TORO TQF WALTZ-16 Saturation-Recovery 饱和恢复Time Correlation Function 时间相关涵数Total Correlation Spectroscopy 全(总)相关谱TOCSY-ROESY Relay TOCSY-ROESY 接力Triple-Quantum Filter 三量子滤波A broadband decoupling sequence 宽带去偶序列WATERGATE Water suppression pulse sequence 水峰压制脉冲序列WEFTZQ(C) ZQF T1T2 tmWater Eliminated Fourier Transform 水峰消除傅立叶变换Zero-Quantum (Coherence) 零量子相干Zero-Quantum Filter 零量子滤波Longitudinal (spin-lattice) relaxation time for MZ 纵向(自旋- 晶格)弛豫时间Transverse (spin-spin) relaxation time for Mxy 横向(自旋-自旋)弛豫时间T C rotational correlation time 旋转相关时间。
径向基神经网络相关函数:dist、netprod、dotprod
径向基神经⽹络相关函数:dist、netprod、dotprod (1) dist 欧⼏⾥得距离权函数This MATLAB function takes these inputs, W S-by-R weight matrixP R-by-Q matrix ofQ input (column) vectors FPStruct of function parameters (optional, ignored)Z = dist(W,P,FP)dim = dist('size',S,R,FP)dw = dist('dw',W,P,Z,FP)D = dist(pos)info = dist('code')W中每⾏为⼀个输⼊向量,P中每列为⼀个输⼊向量>> w=rand(2,3)w =0.8705 0.1909 0.42290.8706 0.7651 0.5156>> v=rand(3,6)v =0.5917 0.1118 0.3500 0.2799 0.3541 0.22670.7005 0.7944 0.8652 0.2283 0.8885 0.11610.0203 0.1223 0.2577 0.8963 0.0224 0.7173>> w*vans =0.6574 0.3007 0.5788 0.6662 0.4873 0.52281.0615 0.7682 1.0995 0.8805 0.9996 0.6560>> D=dist(ans) % 只有⼀个输⼊,计算Z中每⼀⾏与其他⾏的距离D =0 0.4618 0.0873 0.1813 0.1810 0.42720.4618 0 0.4326 0.3824 0.2973 0.24880.0873 0.4326 0 0.2359 0.1355 0.44700.1813 0.3824 0.2359 0 0.2150 0.26630.1810 0.2973 0.1355 0.2150 0 0.34540.4272 0.2488 0.4470 0.2663 0.3454 0(2)netprod - Product net input function 乘积⽹格输⼊函数This MATLAB function takes Z iS-by-Q matrices in a row cell arrayN = netprod({Z1,Z2,...,Zn})返回Z1,Z2,...,Zn 对应元素的乘积rand('state',pi);a=rand(2,3) % 第⼀个矩阵% a =%% 0.5162 0.1837 0.4272% 0.2252 0.2163 0.9706b=rand(2,3) % 第⼆个矩阵% b =%% 0.8215 0.0295 0.2471% 0.3693 0.1919 0.5672c=rand(2,3) % 第三个矩阵% c =%% 0.4331 0.0485 0.5087% 0.6111 0.8077 0.3153d=netprod({a,b,c}) % 计算⽹络输⼊% d =%% 0.1837 0.0003 0.0537% 0.0508 0.0335 0.1736a.*b.*c % 矩阵直接点乘%% ans =%% 0.1837 0.0003 0.0537% 0.0508 0.0335 0.1736(3)dotprod>> help dotproddotprod - Dot product weight functionThis MATLAB function takes these inputs, W S-by-R weight matrix PR-by-Q matrix of Q input (column) vectors FPStruct of function parameters (optional, ignored) Z = dotprod(W,P,FP)dim = dotprod('size',S,R,FP)dw = dotprod('dw',W,P,Z,FP)info = dotprod('code')rand('state',pi);w=rand(3,2); % 3个向量p=rand(2,4); % 4个向量Z=dotprod(w,p) % 计算内积% Z =%% 0.5039 0.0567 0.2502 0.3557% 0.3428 0.0886 0.2979 0.3586% 0.5094 0.1916 0.5959 0.6726(4)netsum 求和⽹格输⼊函数>> help netsumnetsum - Sum net input functionThis MATLAB function takes Z1 to Zn and optional function parameters, ZiS-by-Q matrices in a row cell array FPRow cell array of function parameters (ignored)N = netsum({Z1,Z2,...,Zn},FP)info = netsum('code')返回对应位置元素相加rand('state',pi);a=rand(2,3)% a =% 0.5162 0.1837 0.4272 % 0.2252 0.2163 0.9706 b=rand(2,3)% b =% 0.8215 0.0295 0.2471 % 0.3693 0.1919 0.5672 c=[0; -1];d=concur(c,3)% d =% 0 0 0% -1 -1 -1n = netsum({a,b,d})% n =% 1.3377 0.2132 0.6743 % -0.4054 -0.5918 0.5378。
原始图与三次图的可圈度(英文)
原始图与三次图的可圈度(英文)
宝升;王海荣
【期刊名称】《数学研究》
【年(卷),期】1996(000)002
【摘要】无
【总页数】1页(P5)
【作者】宝升;王海荣
【作者单位】无
【正文语种】中文
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2.三次图的完全扩容图的连通度 [J], 萨如拉;阿勇嘎
3.给定度序列的三圈图的极值图 [J], 杨杨;邵燕灵
4.三圈图和四圈图的最大无符号拉普拉斯分离度 [J], 剧宏娟;雷英杰
5.图的圈边连通度和圈弧连通度 [J], 朱虹州;孟吉翔
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Abstract
1 Introduction
Code division multiple access (CDMA) has emerged as one of the most promising technologies for meeting the challenges of the physical network layer, as evident from its
This research was supported in part by the Wisconsin Alumni Research Foundation.
1
prominence in the wireless infrastructure envisioned for the third and future generation systems. Innovative DSP techniques are playing a progressively important role in the design of CDMA systems due to the high complexity of processing required in the physical layer. The major DSP challenges in CDMA system design stem from three key factors that have a signi cant impact on performance: Channel propagation dynamics manifested as multipath dispersion, multipath fading, and temporal variations or Doppler e ects. Multiaccess interference due to multiple simultaneous users, which is further accentuated by multipath propagation e ects. Complexity of the DSP algorithms. Even though the above factors are clearly interrelated, existing techniques re ect a piecemeal approach due to the lack of a framework connecting the various physical layer facets. In contrast, the progressively stringent performance demands imposed by future wireless systems dictate an integrated approach to deliver fully optimized systems. In this paper, we propose DSP in canonical multipath-Doppler coordinates as an integrated framework for combating time-varying multipath distortion, suppressing multiaccess interference, and managing the complexity of the resulting algorithms. The canonical coordinates are derived from a fundamental characterization of the channel propagation dynamics in terms of discrete multipath-delayed and Doppler-shifted copies of the transmitted spread-spectrum waveform which constitute a xed canonical basis for representing the received signal 1]. A well-known advantage of CDMA, by virtue of spread-spectrum signaling, is its remarkable ability to combat fading by exploiting multipath propagation e ects 2]. Our framework promises a new DSP innovation: further exploiting the time-varying multipath e ects to suppress multiaccess interference via subspace-based processing in the canonical coordinates. The next section introduces the generic receiver structure in the canonical coordinates. Section 2 describes the fundamental channel characterization that underlies the proposed framework. Sections 4 and 5 discuss the basic ideas behind receiver design in canonical coordinates, emphasizing channel modeling and interference suppression issues. Concluding remarks are presented in Section 6.
2 The Canonical Coordinates
Figure 1 describes DSP in canonical multipath-Doppler coordinates that is at the heart of our framework. The front-end processing corresponds to projecting the received waveform onto the canonical coordinates. Each user corresponds to unique coordinates de ned by its spreading code, which are computed for each received symbol. Canonical coordinates, taken together for all users and symbols of interest, constitute su cient statistics for demodulation|all DSP can be performed in the canonical coordinates. The coordinates for each symbol of a particular user are computed by correlating the received signal with time- and frequency-shifted copies of the user spreading waveform ! Z l e?j 2 Tmt dt; zml = r(t)q t ? o ? B (1) l = 0; ; L ; m = ?M; ; 0; ; M; where r(t) denotes the received waveform, o denotes the user delay, and q(t) is the user spreading waveform of duration T and bandwidth B . In e ect, the canonical multipath2
Canonical Multipath-Doppler CoordinatБайду номын сангаасs in Wireless Communications
Akbar M. Sayeed
Department of Electrical and Computer Engineering University of Wisconsin{Madison 1415 Engineering Drive Madison, WI 53706 akbar@ Tel: (608) 265-4731, Fax: (608) 262-1267 /ece/ 36th Annual Allerton Conference, September 1998.
Code division multiple access (CDMA) has emerged as a dominant technology for meeting the physical layer challenges of future wireless communication systems. Signal processing requirements in the physical layer are dictated by three major factors: multiaccess interference, multipath dispersion and fading, and transceiver complexity. Existing CDMA system designs re ect a piecemeal approach due to the lack of an e ective framework for jointly addressing these issues. We propose signal processing in canonical multipath-Doppler coordinates for attacking physical layer impairments in an integrated fashion. The canonical coordinates are derived from a fundamental characterization of channel propagation dynamics in terms of discrete multipath-delayed and Doppler-shifted copies of the spread-spectrum signaling waveforms. The multipath-Doppler shifted waveforms constitute an approximately orthogonal basis and the corresponding signal representation naturally connects the various channel e ects. First, all processing relating to multipath propagation can be directly performed in the canonical coordinates. Second, the same coordinates provide a canonical subspace-based representation of the desired signal and interference which fully incorporates channel dispersion e ects. Finally, the maximally parsimonious nature of the coordinates and their simple computation a ord a direct handle on transceiver complexity. Various facets of the integrated framework are illustrated in the context of interference suppression, channel estimation, and diversity processing.