Use MATLAB to solve linear programs Optimization M

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最完整的MATLAB工具箱的链接

最完整的MATLAB工具箱的链接

MATLAB Toolboxestop Audio - Astronomy - BioMedicalInformatics - Chemometrics - Chaos - Chemistry - Coding - Control - Communications - Engineering - Excel - FEM - Finance - GAs - Graphics - Images - ICA - Kernel - Markov - Medical - MIDI - Misc. - MPI - NNets - Oceanography - Optimization - Plot - Signal Processing - Optimization - Statistics - SVM - etc ...NewZSM (zero sum multinomial)/zsmcode.htmlBinaural-modeling software for MATLAB/Windows/home/Michael_Akeroyd/download2.ht mlStatistical Parametric Mapping (SPM)/spm/ext/BOOTSTRAP MATLAB TOOLBOX.au/downloads/bootstrap_toolbox.htmlThe DSS package for MATLABDSS Matlab package contains algorithms for performing linear, deflation and symmetric DSS.http://www.cis.hut.fi/projects/dss/package/Psychtoolbox/download.htmlMultisurface Method Tree with MATLAB/~olvi/uwmp/msmt.htmlA Matlab Toolbox for every single topic !/~baum/toolboxes.htmleg. BrainStorm - MEG and EEG data visualization and processing CLAWPACK is a software package designed to compute numerical solutionsto hyperbolic partial differential equations using a wave propagation approach/~claw/DIPimage - Image Processing ToolboxPRTools - Pattern Recognition Toolbox (+ Neural Networks)NetLab - Neural Network ToolboxFSTB - Fuzzy Systems ToolboxFusetool - Image Fusion Toolboxhttp://www.metapix.de/toolbox.htmWAVEKIT - Wavelet ToolboxGat - Genetic Algorithm ToolboxTSTOOL is a MATLAB software package for nonlinear time series analysis. TSTOOL can be used for computing: Time-delay reconstruction, Lyapunov exponents, Fractal dimensions, Mutual information, Surrogate data tests, Nearest neighbor statistics, Return times, Poincare sections, Nonlinear predictionhttp://www.physik3.gwdg.de/tstool/MATLAB / Data description toolboxA Matlab toolbox for data description, outlier and novelty detection March 26, 2004 - D.M.J. Taxhttp://www-ict.ewi.tudelft.nl/~davidt/dd_tools/dd_manual.htmlMBEhttp://www.pmarneffei.hku.hk/mbetoolbox/Betabolic network toolbox for Matlabhttp://www.molgen.mpg.de/~lieberme/pages/network_matlab.htmlPharmacokinetics toolbox for Matlabhttp://page.inf.fu-berlin.de/~lieber/seiten/pbpk_toolbox.htmlThe SpiderThe spider is intended to be a complete object orientated environment for machine learning in Matlab. Aside from easy use of base learning algorithms, algorithms can be plugged together and can be comparedwith, e.g model selection, statistical tests and visual plots. This gives all the power of objects (reusability, plug together, share code) but also all the power of Matlab for machine learning research. http://www.kyb.tuebingen.mpg.de/bs/people/spider/index.htmlSchwarz-Christoffel Toolbox/matlabcentral/fileexchange/loadFile.do?o bjectId=1316&objectType=file#XML Toolbox/matlabcentral/fileexchange/loadFile.do?o bjectId=4278&objectType=fileFIR/TDNN Toolbox for MATLABBeta version of a toolbox for FIR (Finite Impulse Response) and TD (Time Delay) Neural Networks./interval-comp/dagstuhl.03/oish.pdfMisc.http://www.dcsc.tudelft.nl/Research/Software/index.htmlAstronomySaturn and Titan trajectories ... MALTAB astronomy/~abrecht/Matlab-codes/AudioMA Toolbox for Matlab Implementing Similarity Measures for Audio http://www.oefai.at/~elias/ma/index.htmlMAD - Matlab Auditory Demonstrations/~martin/MAD/docs/mad.htmMusic Analysis - Toolbox for Matlab : Feature Extraction from Raw Audio Signals for Content-Based Music Retrievalhttp://www.ai.univie.ac.at/~elias/ma/WarpTB - Matlab Toolbox for Warped DSPBy Aki Härmä and Matti Karjalainenhttp://www.acoustics.hut.fi/software/warp/MATLAB-related Softwarehttp://www.dpmi.tu-graz.ac.at/~schloegl/matlab/Biomedical Signal data formats (EEG machine specific file formats with Matlab import routines)http://www.dpmi.tu-graz.ac.at/~schloegl/matlab/eeg/MPEG Encoding library for MATLAB Movies (Created by David Foti)It enables MATLAB users to read (MPGREAD) or write (MPGWRITE) MPEG movies. That should help Video Quality project.Filter Design packagehttp://www.ee.ryerson.ca:8080/~mzeytin/dfp/index.htmlOctave by Christophe COUVREUR (Generates normalized A-weigthing, C-weighting, octave and one-third-octave digital filters)/matlabcentral/fileexchange/loadFile.do?o bjectType=file&objectId=69Source Coding MATLAB Toolbox/users/kieffer/programs.htmlBio Medical Informatics (Top)CGH-Plotter: MATLAB Toolbox for CGH-data AnalysisCode: http://sigwww.cs.tut.fi/TICSP/CGH-Plotter/Poster:http://sigwww.cs.tut.fi/TICSP/CSB2003/Posteri_CGH_Plotter.pdfThe Brain Imaging Software Toolboxhttp://www.bic.mni.mcgill.ca/software/MRI Brain Segmentation/matlabcentral/fileexchange/loadFile.do?o bjectId=4879Chemometrics (providing PCA) (Top)Matlab Molecular Biology & Evolution Toolbox(Toolbox Enables Evolutionary Biologists to Analyze and View DNA and Protein Sequences)James J. Caihttp://www.pmarneffei.hku.hk/mbetoolbox/Toolbox provided by Prof. Massart research grouphttp://minf.vub.ac.be/~fabi/publiek/Useful collection of routines from Prof age smilde research group http://www-its.chem.uva.nl/research/pacMultivariate Toolbox written by Rune Mathisen/~mvartools/index.htmlMatlab code and datasetshttp://www.acc.umu.se/~tnkjtg/chemometrics/dataset.htmlChaos (Top)Chaotic Systems Toolbox/matlabcentral/fileexchange/loadFile.do?o bjectId=1597&objectType=file#HOSA Toolboxhttp://www.mathworks.nl/matlabcentral/fileexchange/loadFile.do?ob jectId=3013&objectType=fileChemistry (Top)MetMAP - (Metabolical Modeling, Analysis and oPtimization alias Met. M. A. P.)http://webpages.ull.es/users/sympbst/pag_ing/pag_metmap/index.htmDoseLab - A set of software programs for quantitative comparison of measured and computed radiation dose distributionsGenBank Overview/Genbank/GenbankOverview.htmlMatlab:/matlabcentral/fileexchange/loadFile.do?o bjectId=1139CodingCode for the estimation of Scaling Exponentshttp://www.cubinlab.ee.mu.oz.au/~darryl/secondorder_code.html Control (Top)Control Tutorial for Matlab/group/ctm/AnotherCommunications (Top)Channel Learning Architecture toolbox(This Matlab toolbox is a supplement to the article "HiperLearn: A High Performance Learning Architecture")http://www.isy.liu.se/cvl/Projects/hiperlearn/Source Coding MATLAB Toolbox/users/kieffer/programs.htmlTCP/UDP/IP Toolbox 2.0.4/matlabcentral/fileexchange/loadFile.do?o bjectId=345&objectType=fileHome Networking Basis: Transmission Environments and Wired/Wireless ProtocolsWalter Y. Chen/support/books/book5295.jsp?category=new& language=-1MATLAB M-files and Simulink models/matlabcentral/fileexchange/loadFile.do?o bjectId=3834&objectType=fileEngineering (Top)OPNML/MATLAB Facilities/OPNML_Matlab/Mesh Generation/home/vavasis/qmg-home.htmlOpenFEM : An Open-Source Finite Element Toolbox/CALFEM is an interactive computer program for teaching the finite element method (FEM)http://www.byggmek.lth.se/Calfem/frinfo.htmThe Engineering Vibration Toolbox/people/faculty/jslater/vtoolbox/vtoolbox .htmlSaGA - Spatial and Geometric Analysis Toolboxby Kirill K. Pankratov/~glenn/kirill/saga.htmlMexCDF and NetCDF Toolbox For Matlab-5&6/staffpages/cdenham/public_html/MexCDF/nc4ml5.htmlCUEDSID: Cambridge University System Identification Toolbox/jmm/cuedsid/Kriging Toolbox/software/Geostats_software/MATLAB_KRIG ING_TOOLBOX.htmMonte Carlo (Dr Nando)http://www.cs.ubc.ca/~nando/software.htmlRIOTS - The Most Powerful Optimal Control Problem Solver/~adam/RIOTS/ExcelMATLAB xlsheets/matlabcentral/fileexchange/loadFile.do?o bjectId=4474&objectType=filewrite2excel/matlabcentral/fileexchange/loadFile.do?o bjectId=4414&objectType=fileFinite Element Modeling (FEM) (Top)OpenFEM - An Open-Source Finite Element Toolbox/NLFET - nonlinear finite element toolbox for MATLAB ( framework for setting up, solving, and interpreting results for nonlinear static and dynamic finite element analysis.)/GetFEM - C++ library for finite element methods elementary computations with a Matlab interfacehttp://www.gmm.insa-tlse.fr/getfem/FELIPE - FEA package to view results ( contains neat interface to MATLA /~blstmbr/felipe/Finance (Top)A NEW MATLAB-BASED TOOLBOX FOR COMPUTER AIDED DYNAMIC TECHNICAL TRADING Stephanos Papadamou and George StephanidesDepartment of Applied Informatics, University Of Macedonia Economic & Social Sciences, Thessaloniki, Greece/fen31/one_time_articles/dynamic_tech_trade_ matlab6.htmPaper::8089/eps/prog/papers/0201/0201001.pdfCompEcon Toolbox for Matlab/~pfackler/compecon/toolbox.htmlGenetic Algorithms (Top)The Genetic Algorithm Optimization Toolbox (GAOT) for Matlab 5 /mirage/GAToolBox/gaot/Genetic Algorithm ToolboxWritten & distributed by Andy Chipperfield (Sheffield University, UK) /uni/projects/gaipp/gatbx.htmlManual: /~gaipp/ga-toolbox/manual.pdfGenetic and Evolutionary Algorithm Toolbox (GEATbx)Evolutionary Algorithms for MATLAB/links/ea_matlab.htmlGenetic/Evolutionary Algorithms for MATLABhttp://www.systemtechnik.tu-ilmenau.de/~pohlheim/EA_Matlab/ea_mat lab.htmlGraphicsVideoToolbox (C routines for visual psychophysics on Macs by Denis Pelli)/VideoToolbox/Paper: /pelli/pubs/pelli1997videotoolbox.pdf4D toolbox/~daniel/links/matlab/4DToolbox.htmlImages (Top)Eyelink Toolbox/eyelinktoolbox/Paper: /eyelinktoolbox/EyelinkToolbox.pdfCellStats: Automated statistical analysis of color-stained cell images in Matlabhttp://sigwww.cs.tut.fi/TICSP/CellStats/SDC Morphology Toolbox for MATLAB (powerful collection of latest state-of-the-art gray-scale morphological tools that can be applied to image segmentation, non-linear filtering, pattern recognition and image analysis)/Image Acquisition Toolbox/products/imaq/Halftoning Toolbox for MATLAB/~bevans/projects/halftoning/toolbox/ind ex.htmlDIPimage - A Scientific Image Processing Toolbox for MATLABhttp://www.ph.tn.tudelft.nl/DIPlib/dipimage_1.htmlPNM Toolboxhttp://home.online.no/~pjacklam/matlab/software/pnm/index.html AnotherICA / KICA and KPCA (Top)ICA TU Toolboxhttp://mole.imm.dtu.dk/toolbox/menu.htmlMISEP Linear and Nonlinear ICA Toolboxhttp://neural.inesc-id.pt/~lba/ica/mitoolbox.htmlKernel Independant Component Analysis/~fbach/kernel-ica/index.htmMatlab: kernel-ica version 1.2KPCA- Please check the software section of kernel machines.KernelStatistical Pattern Recognition Toolboxhttp://cmp.felk.cvut.cz/~xfrancv/stprtool/MATLABArsenal A MATLAB Wrapper for Classification/tmp/MATLABArsenal.htmMarkov (Top)MapHMMBOX 1.1 - Matlab toolbox for Hidden Markov Modelling using Max. Aposteriori EMPrerequisites: Matlab 5.0, Netlab. Last Updated: 18 March 2002. /~parg/software/maphmmbox_1_1.tarHMMBOX 4.1 - Matlab toolbox for Hidden Markov Modelling using Variational BayesPrerequisites: Matlab 5.0,Netlab. Last Updated: 15 February 2002.. /~parg/software/hmmbox_3_2.tar/~parg/software/hmmbox_4_1.tarMarkov Decision Process (MDP) Toolbox for MatlabKevin Murphy, 1999/~murphyk/Software/MDP/MDP.zipMarkov Decision Process (MDP) Toolbox v1.0 for MATLABhttp://www.inra.fr/bia/T/MDPtoolbox/Hidden Markov Model (HMM) Toolbox for Matlab/~murphyk/Software/HMM/hmm.htmlBayes Net Toolbox for Matlab/~murphyk/Software/BNT/bnt.htmlMedical (Top)EEGLAB Open Source Matlab Toolbox for Physiological Research (formerly ICA/EEG Matlab toolbox)/~scott/ica.htmlMATLAB Biomedical Signal Processing Toolbox/Toolbox/Powerful package for neurophysiological data analysis ( Igor Kagan webpage)/Matlab/Unitret.htmlEEG / MRI Matlab Toolbox/Microarray data analysis toolbox (MDAT): for normalization, adjustment and analysis of gene expression data.Knowlton N, Dozmorov IM, Centola M. Department of Arthritis andImmunology, Oklahoma Medical Research Foundation, Oklahoma City, OK, USA 73104. We introduce a novel Matlab toolbox for microarray data analysis. This toolbox uses normalization based upon a normally distributed background and differential gene expression based on 5 statistical measures. The objects in this toolbox are open source and can be implemented to suit your application. AVAILABILITY: MDAT v1.0 is a Matlab toolbox and requires Matlab to run. MDAT is freely available at:/publications/2004/knowlton/MDAT.zip MIDI (Top)MIDI Toolbox version 1.0 (GNU General Public License)http://www.jyu.fi/musica/miditoolbox/Misc. (Top)MATLAB-The Graphing Tool/~abrecht/matlab.html3-D Circuits The Circuit Animation Toolbox for MATLAB/other/3Dcircuits/SendMailhttp://carol.wins.uva.nl/~portegie/matlab/sendmail/Coolplothttp://www.reimeika.ca/marco/matlab/coolplots.htmlMPI (Matlab Parallel Interface)Cornell Multitask Toolbox for MATLAB/Services/Software/CMTM/Beolab Toolbox for v6.5Thomas Abrahamsson (Professor, Chalmers University of Technology, Applied Mechanics, Göteborg, Sweden)http://www.mathworks.nl/matlabcentral/fileexchange/loadFile.do?ob jectId=1216&objectType=filePARMATLABNeural Networks (Top)SOM Toolboxhttp://www.cis.hut.fi/projects/somtoolbox/Bayes Net Toolbox for Matlab/~murphyk/Software/BNT/bnt.htmlNetLab/netlab/Random Neural Networks/~ahossam/rnnsimv2/ftp: ftp:///pub/contrib/v5/nnet/rnnsimv2/NNSYSID Toolbox (tools for neural network based identification of nonlinear dynamic systems)http://www.iau.dtu.dk/research/control/nnsysid.htmlOceanography (Top)WAFO. Wave Analysis for Fatigue and Oceanographyhttp://www.maths.lth.se/matstat/wafo/ADCP toolbox for MATLAB (USGS, USA)Presented at the Hydroacoustics Workshop in Tampa and at ADCP's in Action in San Diego/operations/stg/pubs/ADCPtoolsSEA-MAT - Matlab Tools for Oceanographic AnalysisA collaborative effort to organize and distribute Matlab tools for the Oceanographic Community/Ocean Toolboxhttp://www.mar.dfo-mpo.gc.ca/science/ocean/epsonde/programming.htmlEUGENE D. GALLAGHER(Associate Professor, Environmental, Coastal & Ocean Sciences) /edgwebp.htmOptimization (Top)MODCONS - a MATLAB Toolbox for Multi-Objective Control System Design /mecheng/jfw/modcons.htmlLazy Learning Packagehttp://iridia.ulb.ac.be/~lazy/SDPT3 version 3.02 -- a MATLAB software for semidefinite-quadratic-linear programming.sg/~mattohkc/sdpt3.htmlMinimum Enclosing Balls: Matlab Code/meb/SOSTOOLS Sum of Squares Optimization Toolbox for MATLAB User’s guide /sostools/sostools.pdfPSOt - a Particle Swarm Optimization Toolbox for use with MatlabBy Brian Birge ... A Particle Swarm Optimization Toolbox (PSOt) for use with the Matlab scientific programming environment has been developed. PSO isintroduced briefly and then the use of the toolbox is explained with some examples. A link to downloadable code is provided.Plot/software/plotting/gbplot/Signal Processing (Top)Filter Design with Motorola DSP56Khttp://www.ee.ryerson.ca:8080/~mzeytin/dfp/index.htmlChange Detection and Adaptive Filtering Toolboxhttp://www.sigmoid.se/Signal Processing Toolbox/products/signal/ICA TU Toolboxhttp://mole.imm.dtu.dk/toolbox/menu.htmlTime-Frequency Toolbox for Matlabhttp://crttsn.univ-nantes.fr/~auger/tftb.htmlVoiceBox - Speech Processing Toolbox/hp/staff/dmb/voicebox/voicebox.htmlLeast Squared - Support Vector Machines (LS-SVM)http://www.esat.kuleuven.ac.be/sista/lssvmlab/WaveLab802 : the Wavelet ToolboxBy David Donoho, Mark Reynold Duncan, Xiaoming Huo, Ofer Levi /~wavelab/Time-series Matlab scriptshttp://wise-obs.tau.ac.il/~eran/MATLAB/TimeseriesCon.htmlUvi_Wave Wavelet Toolbox Home Pagehttp://www.gts.tsc.uvigo.es/~wavelets/index.htmlAnotherSupport Vector Machine (Top)MATLAB Support Vector Machine ToolboxDr Gavin CawleySchool of Information Systems, University of East Anglia/~gcc/svm/toolbox/LS-SVM - SISTASVM toolboxes/dmi/svm/LSVM Lagrangian Support Vector Machine/dmi/lsvm/Statistics (Top)Logistic regression/SAGA/software/saga/Multi-Parametric Toolbox (MPT) A tool (not only) for multi-parametric optimization.http://control.ee.ethz.ch/~mpt/ARfit: A Matlab package for the estimation of parameters and eigenmodes of multivariate autoregressive modelshttp://www.mat.univie.ac.at/~neum/software/arfit/The Dimensional Analysis Toolbox for MATLABHome: http://www.sbrs.de/Paper:http://www.isd.uni-stuttgart.de/~brueckner/Papers/similarity2002. pdfFATHOM for Matlab/personal/djones/PLS-toolboxMultivariate analysis toolbox (N-way Toolbox - paper)http://www.models.kvl.dk/source/nwaytoolbox/index.aspClassification Toolbox for Matlabhttp://tiger.technion.ac.il/~eladyt/classification/index.htmMatlab toolbox for Robust Calibrationhttp://www.wis.kuleuven.ac.be/stat/robust/toolbox.htmlStatistical Parametric Mapping/spm/spm2.htmlEVIM: A Software Package for Extreme Value Analysis in Matlabby Ramazan Gençay, Faruk Selcuk and Abdurrahman Ulugulyagci, 2001. Manual (pdf file) evim.pdf - Software (zip file) evim.zipTime Series Analysishttp://www.dpmi.tu-graz.ac.at/~schloegl/matlab/tsa/Bayes Net Toolbox for MatlabWritten by Kevin Murphy/~murphyk/Software/BNT/bnt.htmlOther: /information/toolboxes.htmlARfit: A Matlab package for the estimation of parameters and eigenmodes of multivariate autoregressive models/~tapio/arfit/M-Fithttp://www.ill.fr/tas/matlab/doc/mfit4/mfit.htmlDimensional Analysis Toolbox for Matlab/The NaN-toolbox: A statistic-toolbox for Octave and Matlab® ... handles data with and without MISSING VALUES.http://www-dpmi.tu-graz.ac.at/~schloegl/matlab/NaN/Iterative Methods for Optimization: Matlab Codes/~ctk/matlab_darts.htmlMultiscale Shape Analysis (MSA) Matlab Toolbox 2000p.br/~cesar/projects/multiscale/Multivariate Ecological & Oceanographic Data Analysis (FATHOM) From David Jones/personal/djones/glmlab (Generalized Linear Models in MATLA.au/staff/dunn/glmlab/glmlab.html Spacial and Geometric Analysis (SaGA) toolboxInteresting audio links with FAQ, VC++, on the topicMATLAB Toolboxes(C) 2004 - SPMC / SoCCE / UoP。

matlab求解常微分方程

matlab求解常微分方程

用matlab 求解常微分方程在MATLAB 中,由函数dsolve ()解决常微分方程(组)的求解问题,其具体格式如下:r = dsolve('eq1,eq2,...', 'cond1,cond2,...', 'v')'eq1,eq2,...'为微分方程或微分方程组,'cond1,cond2,...',是初始条件或边界条件,'v'是独立变量,默认的独立变量是't'。

函数dsolve 用来解符号常微分方程、方程组,如果没有初始条件,则求出通解,如果有初始条件,则求出特解。

例1:求解常微分方程1dy dx x y =+的MATLAB 程序为:dsolve('Dy=1/(x+y)','x') ,注意,系统缺省的自变量为t ,因此这里要把自变量写明。

其中:Y=lambertw(X)表示函数关系Y*exp(Y)=X 。

例2:求解常微分方程2'''0yy y -=的MATLAB 程序为:Y2=dsolve('y*D2y-Dy^2=0','x')Y2=dsolve('D2y*y-Dy^2=0','x')我们看到有两个解,其中一个是常数0。

例3:求常微分方程组253ttdxx y edtdyx y edt⎧++=⎪⎪⎨⎪--=⎪⎩通解的MATLAB程序为:[X,Y]=dsolve('Dx+5*x+y=exp(t),Dy-x-3*y=exp(2*t)','t')例4:求常微分方程组2210cos,224,0tttdx dyx t xdt dtdx dyy e ydt dt=-=⎧+-==⎪⎪⎨⎪++==⎪⎩通解的MATLAB程序为:[X,Y]=dsolve('Dx+2*x-Dy=10*cos(t),Dx+Dy+2*y=4*exp(-2*t)','x(0)=2,y(0)=0','t')以上这些都是常微分方程的精确解法,也称为常微分方程的符号解。

图像处理英文翻译

图像处理英文翻译

数字图像处理英文翻译(Matlab帮助信息简介)xxxxxxxxx xxx IntroductionMATLAB is a high-level technical computing language and interactive environment for algorithm development, data visualization, data analysis, and numeric computation. Using the MATLAB product, you can solve technical computing problems faster than with traditional programming languages, such as C, C++, and Fortran.You can use MATLAB in a wide range of applications, including signal and image processing, communications, control design, test and measurement, financial modeling and analysis, and computational biology. Add-on toolboxes (collections of special-purpose MATLAB functions, available separately) extend the MATLAB environment to solve particular classes of problems in these application areas.The MATLAB system consists of these main parts:Desktop Tools and Development EnvironmentThis part of MATLAB is the set of tools and facilities that help you use and become more productive with MATLAB functions and files. Many of these tools are graphical user interfaces. It includes: theMATLAB desktop and Command Window, an editor and debugger, a code analyzer, and browsers for viewing help, the workspace, and folders. Mathematical Function LibraryThis library is a vast collection of computational algorithms ranging from elementary functions, like sum, sine, cosine, and complex arithmetic, to more sophisticated functions like matrix inverse, matrix eigenvalues, Bessel functions, and fast Fourier transforms.The LanguageThe MATLAB language is a high-level matrix/array language with control flow statements, functions, data structures, input/output, and object-oriented programming features. It allows both "programming in the small" to rapidly create quick programs you do not intend to reuse. You can also do "programming in the large" to create complex application programs intended for reuse.GraphicsMATLAB has extensive facilities for displaying vectors and matrices as graphs, as well as annotating and printing these graphs. It includes high-level functions for two-dimensional and three-dimensional data visualization, image processing, animation, and presentation graphics. Italso includes low-level functions that allow you to fully customize the appearance of graphics as well as to build complete graphical user interfaces on your MATLAB applications.External InterfacesThe external interfaces library allows you to write C/C++ and Fortran programs that interact with MATLAB. It includes facilities for calling routines from MATLAB (dynamic linking), for calling MATLAB as a computational engine, and for reading and writing MAT-files.MATLAB provides a number of features for documenting and sharing your work. You can integrate your MATLAB code with other languages and applications, and distribute your MATLAB algorithms and applications. Features include:High-level language for technical computingDevelopment environment for managing code, files, and dataInteractive tools for iterative exploration, design, and problem solving Mathematical functions for linear algebra, statistics, Fourier analysis, filtering, optimization, and numerical integration2-D and 3-D graphics functions for visualizing dataTools for building custom graphical user interfacesFunctions for integrating MATLAB based algorithms with external appli cations and languages, such as C, C++, Fortran, Java™, COM, andMicrosoft® ExcelThe basic data structure in MATLAB is the array, an ordered set of real or complex elements. This object is naturally suited to the representation of images, real-valued ordered sets of color or intensity data.MATLAB stores most images as two-dimensional arrays (i.e., matrices), in which each element of the matrix corresponds to a single pixel in the displayed image. (Pixel is derived from picture element and usually denotes a single dot on a computer display.)For example, an image composed of 200 rows and 300 columns of different colored dots would be stored in MATLAB as a 200-by-300 matrix. Some images, such as truecolor images, require a three-dimensional array, where the first plane in the third dimension represents the red pixel intensities, the second plane represents the green pixel intensities, and the third plane represents the blue pixel intensities. This convention makes working with images in MATLAB similar to working with any other type of matrix data, and makes the full power of MATLAB available for image processing applications.The Image Processing Toolbox software is a collection of functions that extend the capability of the MATLAB numeric computing environment. The toolbox supports a wide range of image processing operations, includingSpatial image transformationsMorphological operationsNeighborhood and block operationsLinear filtering and filter designTransformsImage analysis and enhancementImage registrationDeblurringRegion of interest operationsMany of the toolbox functions are MATLAB files with a series of MATLAB statements that implement specialized image processing algorithms. You can view the MATLAB code for these functions using the statement:type function_nameYou can extend the capabilities of the toolbox by writing your own files, or by using the toolbox in combination with other toolboxes, such as the Signal Processing Toolbox™ software and the Wavelet Toolbox™ software.Configuration NotesTo determine if the Image Processing Toolbox software is installed on your system, type this command at the MATLAB prompt.verWhen you enter this command, MATLAB displays information about the version of MATLAB you are running, including a list of all toolboxes installed on your system and their version numbers.For information about installing the toolbox, see the installation guide.For the most up-to-date information about system requirements, see the system requirements page, available in the products area at the MathWorks Web site ().Related ProductsMathWorks provides several products that are relevant to the kinds of tasks you can perform with the Image Processing Toolbox software and that extend the capabilities of MATLAB. For information about these related products, see /products/image/related.html. CompilabilityThe Image Processing Toolbox software is compilable with the MATLAB Compiler except for the following functions that launch GUIs cpselectimplayimtool。

MATLAB软件Linprog函数帮助

MATLAB软件Linprog函数帮助

Optimization ToolboxlinprogSolve a linear programming problemEquationwhere f, x, b, beq, lb, and ub are vectors and A and Aeq are matrices.Syntaxx = linprog(f,A,b)x = linprog(f,A,b,Aeq,beq)x = linprog(f,A,b,Aeq,beq,lb,ub)x = linprog(f,A,b,Aeq,beq,lb,ub,x0)x = linprog(f,A,b,Aeq,beq,lb,ub,x0,options)[x,fval] = linprog(...)[x,lambda,exitflag] = linprog(...)[x,lambda,exitflag,output] = linprog(...)[x,fval,exitflag,output,lambda] = linprog(...)Descriptionlinprog solves linear programming problems.x = linprog(f,A,b) solves min f'*x such that A*x <= b.x = linprog(f,A,b,Aeq,beq) solves the problem above while additionally satisfying the equality constraints Aeq*x = beq. Set A=[] and b=[] if no inequalities exist.x = linprog(f,A,b,Aeq,beq,lb,ub) defines a set of lower and upper bounds on the design variables, x, so that the solution is always in the range lb <= x <= ub. Set Aeq=[] and beq=[] if no equalities exist.x = linprog(f,A,b,Aeq,beq,lb,ub,x0) sets the starting point to x0. This option is only available with the medium-scale algorithm (the LargeScale option is set to 'off' using optimset). The default large-scale algorithm and the simplex algorithm ignore any starting point.x = linprog(f,A,b,Aeq,beq,lb,ub,x0,options) minimizes with the optimization options specified in the structure options. Use optimset to set these options.[x,fval] = linprog(...) returns the value of the objective function f un at the solution x: fval =f'*x.[x,lambda,exitflag] = linprog(...) returns a value exitflag that describes the exit condition.[x,lambda,exitflag,output] = linprog(...) returns a structure output that contains information about the optimization.[x,fval,exitflag,output,lambda] = linprog(...) returns a structure lambda whose fields contain the Lagrange multipliers at the solution x.Input ArgumentsFunction Arguments contains general descriptions of arguments passed in to linprog. Options provides the function-specific details for the options values.Output ArgumentsFunction Arguments contains general descriptions of arguments returned by linprog. This section provides function-specific details for exitflag, lambda, and output:exitflag Integer identifying the reason the algorithm terminated. Thefollowing lists the values of exitflag and the correspondingreasons the algorithm terminated.1Function converged to a solution x.0Number of iterations exceededoptions.MaxIter.-2No feasible point was found.-3Problem is unbounded.-4NaN value was encountered duringexecution of the algorithm.-5Both primal and dual problems areinfeasible.-7Search direction became too small. Nofurther progress could be made.lambda Structure containing the Lagrange multipliers at the solution x(separated by constraint type). The fields of the structure are:lower Lower bounds lbupper Upper bounds ubineqlin Linear inequalitieseqlin Linear equalitiesoutput Structure containing information about the optimization. Thefields of the structure are:algorithm Algorithm usedcgiterations The number of conjugate gradient iterations(large-scale algorithm only).iterations Number of iterationsmessage Exit messageOptionsOptimization options used by linprog. Some options apply to all algorithms, and others are only relevant when using the large-scale algorithm.You can use optimset to set or change the values of these fields in the options structure, options. See Optimization Options for detailed information.LargeScale Use large-scale algorithm when set to 'on'. Usemedium-scale algorithm when set to 'off'.Medium-Scale and Large-Scale AlgorithmsThese options are used by both the medium-scale and large-scale algorithms: Diagnostics Print diagnostic information about the function to be minimized.Display Level of display. 'off''iter' displays'final' (default) displays just thefinal output. At this time, the 'iter' level only works with thelarge-scale algorithm.MaxIter Maximum number of iterations allowed.Medium-Scale Algorithm OnlyThese options are used by the medium-scale algorithm:Simplex If 'on', linprog uses the simplex algorithm. The simplexalgorithm uses a built-in starting point, ignoring the startingpoint x0 if supplied. The default is 'off'. See SimplexAlgorithm for more information and an example.Large-Scale Algorithm OnlyThese options are used only by the large-scale algorithm:TolFun Termination tolerance on the functionvalue.ExamplesFind x that minimizessubject toFirst, enter the coefficientsA = [1 -1 13 2 4Next, call a linear programming routine.Entering x, lambda.ineqlin, and lambda.lower getsx =0.000015.00003.0000lambda.ineqlin =1.50000.5000lambda.lower =1.0000Nonzero elements of the vectors in the fields of lambda indicate active constraints at the solution. In this case, the second and third inequality constraints (inlambda.ineqlin) and the first lower bound constraint (in lambda.lower) are active constraints (i.e., the solution is on their constraint boundaries).AlgorithmLarge-Scale OptimizationThe large-scale method is based on LIPSOL (Linear Interior Point Solver, [3]), which is a variant of Mehrotra's predictor-corrector algorithm ([2]), a primal-dual interior-point method. A number of preprocessing steps occur before the algorithm begins to iterate. See Large-Scale Linear Programming.Medium-Scale Optimizationlinprog uses a projection method as used in the quadprog algorithm. linprog is an active set method and is thus a variation of the well-known simplex method for linear programming [1]. The algorithm finds an initial feasible solution by first solving another linear programming problem.Alternatively, you can use the simplex algorithm, described in Simplex Algorithm, by enteringoptions = optimset('LargeScale', 'off', 'Simplex', 'on')and passing options as an input argument to linprog. The simplex algorithm returns a vertex optimal solution.DiagnosticsLarge-Scale OptimizationThe first stage of the algorithm might involve some preprocessing of the constraints (see Large-Scale Linear Programming). Several possible conditions might occur that cause linprog to exit with an infeasibility message. In each case, the exitflag argument returned by linprog is set to a negative value to indicate failure.If a row of all zeros is detected in Aeq but the corresponding element of beq is not zero,the exit message isExiting due to infeasibility: An all zero row in the constraint matrix does not have a zero in corresponding right-hand sizeentry.If one of the elements of x is found not to be bounded below, the exit message is Exiting due to infeasibility: Objective f'*x is unbounded below If one of the rows of Aeq has only one nonzero element, the associated value in x iscalled a singleton variable. In this case, the value of that component of x can becomputed from Aeq and beq. If the value computed violates another constraint, the exit message isExiting due to infeasibility: Singleton variables in equalityconstraints are not feasible.If the singleton variable can be solved for but the solution violates the upper or lower bounds, the exit message isExiting due to infeasibility: Singleton variables in the equality constraints are not within bounds.Once the preprocessing has finished, the iterative part of the algorithm begins until the stopping criteria are met. (See Large-Scale Linear Programming for more informationabout residuals, the primal problem, the dual problem, and the related stopping criteria.)If the residuals are growing instead of getting smaller, or the residuals are neithergrowing nor shrinking, one of the two following termination messages is displayed, respectively,One or more of the residuals, duality gap, or total relative erro has grown 100000 times greater than its minimum value so far:orOne or more of the residuals, duality gap, or total relative erro has stalled:After one of these messages is displayed, it is followed by one of the following sixmessages indicating that the dual, the primal, or both appear to be infeasible. The messages differ according to how the infeasibility or unboundedness was measured.The dual appears to be infeasible (and the primal unbounded).(The primal residual < TolFun.)The primal appears to be infeasible (and the dual unbounded). (Th dual residual < TolFun.)The dual appears to be infeasible (and the primal unbounded) sinc the dual residual > sqrt(TolFun).(The primal residual <10*TolFun.)The primal appears to be infeasible (and the dual unbounded) sinc the primal residual > sqrt(TolFun).(The dual residual <10*TolFun.)The dual appears to be infeasible and the primal unbounded since the primal objective < -1e+10 and the dual objective < 1e+6.The primal appears to be infeasible and the dual unbounded since the dual objective > 1e+10 and the primal objective > -1e+6.Both the primal and the dual appear to be infeasible.Note that, for example, the primal (objective) can be unbounded and the primal residual, which is a measure of primal constraint satisfaction, can be small.Medium-Scale Optimizationlinprog gives a warning when the problem is infeasible.there is no feasible solution.In this case, linprog produces a result that minimizes the worst case constraintviolation.When the equality constraints are inconsistent, linprog givesWarning: The equality constraints are overlyUnbounded solutions result in the warningthe constraints are not restrictive enough.In this case, linprog returns a value of x that satisfies the constraints.LimitationsMedium-Scale OptimizationAt this time, the only levels of display, using the Display option in options, are'off' and 'final''iter' is not available.See AlsoquadprogReferences[1] Dantzig, G.B., A. Orden, and P. Wolfe, "Generalized Simplex Method for Minimizinga Linear from Under Linear Inequality Constraints," Pacific Journal Math., Vol. 5, pp. 183-195.[2] Mehrotra, S., "On the Implementation of a Primal-Dual Interior Point Method," SIAM Journal on Optimization, Vol. 2, pp. 575-601, 1992.[3] Zhang, Y., "Solving Large-Scale Linear Programs by Interior-Point Methods Under the MATLAB Environment," Technical Report TR96-01, Department of Mathematics and Statistics, University of Maryland, Baltimore County, Baltimore, MD, July 1995.gangstr lsqcurvefit © 1994-2005 The MathWorks, Inc. Terms of Use Patents Trademarks。

ExcelSolver的用法

ExcelSolver的用法

Excel Solver的用法电脑相关 2009-06-26, 22:13Solver是Excel一个功能非常强大的插件(Add-Ins),可用于工程上、经济学及其它一些学科中各种问题的优化求解,使用起来非常方便,Solver包括(但不限于)以下一些功能:1、线性规划2、非线性规划3、线性回归,多元线性回归可以用Origin求解,也可以用Excel的linest函数或分析工具求解。

4、非线性回归5、求函数在某区间内的极值注意:Solver插件可以用于解决上面这些问题,并不是说上面这些问题Solver 一定可以解决,而且有时候Solver给出的结果也不一定是最优的。

Solver安装方法:Solver是Excel自带的插件,不需要单独下载安装。

但Excel默认是不启用Solver的,启用方法:在"工具"菜单中点击“插件”,在Solver Add-In前面的方框中打勾,然后点OK,Excel会自动加载Solver,一旦启用成功,以后Sovler 就会在"工具"菜单中显示。

Solver求解非线性回归问题的方法:假设X和Y满足这样一个关系:Y=L(1-10-KX),实验测得一组X和Y的值如下:X Y0 00.54 1830.85 2251.50 2862.46 3803.56 4705.00 544求L和K的值。

在Excel中随便假设一组L和K的值,比如都假设为1,以这组假设的值,求出一组Y’,然后再求出一组(X-Y)2的值,再将求出的这组(X-Y)2的值用Sum函数全部加起来(下面的图中,全部加起来结果在$G$22这个单元格中)。

然后点击“工具”菜单中的Solver,将Set Target Cell设为$G$22这个单元格,将By Changing Cells设为$F$8:$F9这两个单元格,即改变L和K的值,Equal To选中Min这项,其他的选项不用理会,如下图:然后点右上角的Solver,$F$8:$F9就会改变,改变之后的值即为优化的L和K 值。

matlab解四元一次方程组

matlab解四元一次方程组

matlab解四元一次方程组Solving a system of four linear equations with four unknowns, also known as a system of quaternary equations, in MATLAB can be a challenging task for many users. However, with the right approach, this can be achieved effectively. One of the key steps in solving such a system is to represent the equations in matrix form, which can then be easily manipulated using MATLAB's matrix operations. By breaking down the complex problem into smaller, manageable parts, users can simplify the process of solving the four-quaternion equation system.在MATLAB中解决一个包含四个未知数的四元线性方程组,也称为四元方程组,对许多用户来说可能是一个具有挑战性的任务。

然而,通过正确的方法,这可以被有效地实现。

解决这样一个系统的关键步骤之一是以矩阵形式表示方程,然后利用MATLAB的矩阵运算进行简单的操作。

通过将复杂的问题分解成小而易处理的部分,用户可以简化解决四元方程组的过程。

Before attempting to solve a system of four quaternary equations in MATLAB, it is crucial to ensure that the equations are linear and independent. This means that each equation should contain at leastone term with a different unknown variable, ensuring that the system has a unique solution. By verifying the linearity and independence of the equations, users can avoid potential errors in their MATLAB calculations and improve the accuracy of their results. This preliminary check is essential for successfully solving a system of four-quaternion equations.在尝试在MATLAB中解决四元方程组之前,确保方程是线性且独立的至关重要。

Matlab求解线性规划和整数规划问题

Matlab求解线性规划和整数规划问题

Matlab求解线性规划和整数规划问题线性规划和整数规划是数学规划中的两个重要分支,广泛应用于运筹学、经济学、工程学等领域。

Matlab作为一种功能强大的数值计算软件,提供了丰富的工具箱和函数,可以方便地求解线性规划和整数规划问题。

一、线性规划问题的求解线性规划问题是在一组线性约束条件下,求解线性目标函数的最优值的问题。

通常可以表示为如下形式的标准线性规划问题:Maximize (or Minimize) Z = c'xSubject to: Ax ≤ bx ≥ 0其中,c是长度为n的目标函数系数向量,x是长度为n的决策变量向量,A是m×n的系数矩阵,b是长度为m的约束条件向量。

在Matlab中,可以使用线性规划工具箱(Linear Programming Toolbox)中的函数linprog来求解线性规划问题。

linprog函数的基本语法如下:[x, fval, exitflag, output, lambda] = linprog(c, A, b, Aeq, beq, lb, ub, x0, options)其中,c是目标函数系数向量,A和b是不等式约束条件的系数矩阵和约束条件向量,Aeq和beq是等式约束条件的系数矩阵和约束条件向量,lb和ub是决策变量的下界和上界,x0是初始解向量,options是求解选项。

linprog函数的输出结果包括最优解x、最优目标函数值fval、退出标志exitflag、输出信息output和拉格朗日乘子lambda。

二、整数规划问题的求解整数规划问题是在线性规划问题的基础上,要求决策变量取整数值的问题。

通常可以表示为如下形式的标准整数规划问题:Maximize (or Minimize) Z = c'xSubjec t to: Ax ≤ bx ≥ 0x为整数在Matlab中,可以使用整数规划工具箱(Integer Programming Toolbox)中的函数intlinprog来求解整数规划问题。

matlab程序设计与应用习题答案

matlab程序设计与应用习题答案

matlab程序设计与应用习题答案Matlab程序设计与应用习题答案Matlab是一种强大的数学软件,被广泛应用于科学计算、数据分析和工程模拟等领域。

无论是学术界还是工业界,Matlab都扮演着重要的角色。

在学习和应用Matlab时,我们常常会遇到一些习题,下面我将为大家提供一些常见习题的解答。

习题一:编写一个Matlab程序,计算一个数列的和。

数列的定义如下:a(1) = 1, a(n) = a(n-1) + 2*n, 其中n大于等于2。

解答一:```matlabfunction sum = calculate_sum(n)a = zeros(1, n);a(1) = 1;for i = 2:na(i) = a(i-1) + 2*i;endsum = sum(a);end```习题二:编写一个Matlab程序,求解一个线性方程组。

方程组的定义如下:2x + 3y + z = 7, 3x - 2y + 2z = 5, x + y - z = 3。

解答二:```matlabfunction [x, y, z] = solve_equations()A = [2, 3, 1; 3, -2, 2; 1, 1, -1];b = [7; 5; 3];solution = A\b;x = solution(1);y = solution(2);z = solution(3);end```习题三:编写一个Matlab程序,实现矩阵的转置操作。

解答三:```matlabfunction transposed_matrix = transpose_matrix(matrix) [m, n] = size(matrix);transposed_matrix = zeros(n, m);for i = 1:mfor j = 1:ntransposed_matrix(j, i) = matrix(i, j);endendend```习题四:编写一个Matlab程序,实现矩阵的相乘操作。

matlab solve 用法

matlab solve 用法

matlab solve 用法Matlab Solve: A Powerful Tool for Solving EquationsMatlab Solve is a versatile function in Matlab that allows users to solve equations numerically. This tool can handle a wide range of mathematical problems, making it a valuable asset for engineers, scientists, and researchers.With Matlab Solve, users can solve both single-variable and multi-variable equations. Whether you have a simple linear equation or a complex system of nonlinear equations, Matlab Solve can provide accurate solutions quickly and efficiently.To use Matlab Solve, you need to be familiar with the basic syntax. The function takes two arguments: the equations to solve and the variables to solve for. For example, if you have a single-variable equation like "x^2 - 5x + 6 = 0," you can use Matlab Solve as follows:```matlabsyms xeq = x^2 - 5*x + 6 == 0;sol = solve(eq, x);```In this case, the "syms x" command declares a symbolic variable x so that Matlab can solve the equation symbolically. The "eq" variable represents the equation we want to solve, and the "sol" variable stores the solution.For a system of equations involving multiple variables, the process is similar. Let's say we have the following system of equations:```2x + 3y = 74x - 5y = 1```To solve this system using Matlab Solve, we can write the following code:```matlabsyms x yeq1 = 2*x + 3*y == 7;eq2 = 4*x - 5*y == 1;sol = solve([eq1, eq2], [x, y]);```In this example, the "solve" function takes two arguments: a vector of equations [eq1, eq2] and a vector of variables [x, y]. The resulting "sol" contains the solutions for the variables x and y.Matlab Solve is not limited to solving linear equations or systems of equations. It can handle nonlinear equations, polynomial equations, and even differential equations. With its built-in algorithms and numerical methods, Matlab Solve can find solutions accurately and efficiently.In conclusion, Matlab Solve is a powerful tool for solving equations in Matlab. It is flexible enough to handle various mathematical problems, from simple to complex. By utilizing Matlab Solve, users can save time and effort in finding numerical solutions to mathematical equations.。

MATLAB实验之线性规划问题求解

MATLAB实验之线性规划问题求解
a)设每天各时间段的所需要的护士为x1,x2,x3,x4,x5,x6
Minz=x1+x2+x3+x4+x5+x6
X6+x1>=12 x1+x2>=10 x2+x3>=15 x3+x4>=25 x4+x5>=20 x5+x6>=18
x1,x2,x3,x4,x5,x6>=0
>> f
b =
-12
-10
-15
-25
-20
-18
vub =
[]
Optimization terminated.
x =
5.1858
4.8142
12.0276
12.9724
8.9118
9.0882
fval =
53.0000
b)设正式工x1,x2,x3,x4,x5,x6人,合同工x1’,x2’,x3’,x4’x5’x6’人。
Minz=(x1+x2+x3+x4+x5+x6)*10*8+(x1’+x2’+x3’+x4’+x5’+x6’)*15*8
4、命令:[x,fval]=linprog(…)
返回最优解x及x处的目标函数值fval.
三,使用仪器,材料
四,实验内容与步骤
五,实验过程原始记录(数据,图表,计算等)
1.求解下列线性规划的解:
>> Untitled
Optimization terminated.
x =
0000
-0.1947
1.0000
18:00~22:00 18人;22:00~2:00 12人。

matlab 英文资料

matlab 英文资料

Matlab is a numerical computing, symbolic computation and graphics processing power in one of the scientific computing language. As a powerful scientific computing platform, it almost to meet all your computing needs. In the United States and other developed countries in the universities of science and technology, Matlab can become a compulsory course, in research institutes, engineering departments of large companies or enterprises, Matlab is one of the most common calculation tools.Matlab has the following advantages and features:Friendly platform and into the environment: with the commercialization of Matlab and the continuous upgrading of the software itself, Matlab user interface is also increasingly delicate, closer to Windows standards interface, human-computer interaction more, operation simple. And new versions of Matlab provides complete online queries, help systems, greatly facilitate the user's use. A simple programming environment provides a more complete debugging system, the program can be run directly without compiled, and able to report errors that occur in a timely manner and the cause of the error analysis.Easy to use programming language: Matlab language is based on the most popular on the basis of the c language, grammatical features and very similar to the c language, but more simple, more in line with the scientific and technical personnel on digital writing format. Make it more conducive to non-computer professional technical personnel to use. And this language very good portability, scalability, and this is a Matlab can go to scientific research and engineering calculation of various areas of important reasons.Powerful scientific computing and data processing capacity: Matlab has more than 600 more engineering used in mathematical operations function, it to easily implement various calculation functions required to support. Function of acid is used in the latest research results in scientific and engineering calculations, and by a variety of optimization and fault-tolerant processing, so use very high robustness and reliability. Typically, you can use it to replace the underlying programming language such as c and C++ languages. In the case of computing requirements are the same as, using Matlab programming effort is greatly reduced. Matlab function to solve the problems included matrix calculations and solution of linear equations, solution of differential equations and partial differential equations, symbols, operations, statistical analysis, Fourier transform and data engineering optimization problems, sparse matrix operations, complex operations, trigonometric functions and other elementary mathematical operations, multidimensional array operations such as modeling and dynamic simulation.Excellent of graphics processing function: Matlab since produced of day up on has convenient of data Visual of function, new version of Matlab on entire graphics processing function do has is large of improved and improve, makes it not only in general data Visual of software are has of function (for example second dimension curve and three dimensional surface of draws and processing,) aspects more perfect, and for some other software no of function (for example graphics of light processing, and chroma processing and four data of performance,), Matlab also performance has excellent of processing ability. Also for some special visual needs, such as graphics, animation, Matlab has a corresponding function, ensuring the user different requirements. In addition, new versions of Matlab also focus on the graphical user interface (GUI) on the making of a great deal of improvement, this support can also have special requirements are met.Widely used set of modules and Toolkit: Matlab for many specialized areas have developed apowerful set of modules or the Toolbox. In General, they are all developed by experts in a particular field, users can simply use the Toolbox to learn, apply and evaluate different methods without the need to write the code yourself. Currently, Matlab has to Toolbox extends to has scientific research and engineering application of many area, such as data acquisition, and database interface, and probability statistics, and sample section intended close, and optimization algorithm, and partial differential equation solution, and neural network, and Wavelet analysis, and signal processing, and figure as processing, and system identification, and control system design, and LMI control, and Lu bar control, and model forecast, and fuzzy logic, and financial analysis, and map tools, and nonlinear control design, and real-time fast prototype and the half in simulation, embedded system development, and fixed-point simulation, and DSP and communications, and power system simulation,, are in Toolbox (Toolbox) family in the has has own of place.Practical program interface and publishing platform: Matlab using the Matlab compiler and C/C++ mathematics and graphics libraries, your own Matlab program automatically converted to Matlab-independent c and C++ code that is running. Matlab mesh services programs also allow in Web applications using their own Matlab mathematics and graphics.Modular design and system-level simulation: Simulink is a branch of the Matlab product, mainly used to achieve the modeling and dynamic simulation of engineering problems. In the context of world-wide wave of modeling, Simulink precisely reflects the modular design and system-level simulation of concrete thinking, making built to imitate is really as easy as taking the plot. Implementation of Simulink simulation can be applied to dynamic systems, design of signal control, communications, financial accounting and in bio-medical and other fields of study.Because Matlab has incomparable advantages over other computer languages, at present it has as an industry standard of engineering and science education. As it became increasingly popularity worldwide, also started to learn Matlab boom in China.Simulink simulation environment is a United States Math Works specifically for Matlab software company in 1990 provides charts of programming language design and simulation of special-purpose software tool, under Matlab6.X as Simulink3.1 above. User program and looks in the simulation environment is the control structure diagram of the system, its operation is based on structure diagram for system simulation. Using Simulink provides of entered signal (signal source module) on structure figure by description of system imposed incentive, using Simulink provides of output device (output interface module) get system of output response data or time response curve, became graphics of, and module of way of control system simulation, makes dynamic system of simulation and built die more simple convenient, this cannot but said is control system simulation tools of a large breakthrough progress.Simulink simulation environment supporting system simulation and modeling of various types, such as linear, nonlinear systems, continuous-time systems, sampling systems, as well as the continuous-discrete hybrid system. In addition, the simulation of sampling system also supports mixing sample rates.Simulink provides graphical user interface (GUI), dragging with the mouse, you can build charts control system in the form of models. Simulink chart module provides a variety of standard library, which mainly include: signal source units, the output device unit, linear unit, linear units and modules, connection unit. Also, open design offers a variety of file s-function design methods, allows users to design their own chart module.Simulink model using graphical system inherited from the bottom up and top down technology. Users can double-click access lower-level modules, to help users understand the internal structure of module Design.Map to Simulink system after the model of system simulation. Implementation of emulator can type models in Matlab platform on which the command file file name to start, or directly by the menu command to start under the Simulink. Simulation operation menu is entirely user interaction, such as simulation algorithm, change the parameter setting, use analog oscilloscope, observation system output or responses within the curve. In addition, the simulation results can be variables, returned later in the Matlab command platform to facilitate the simulation data processing.Simulink simulation performance and simulation accuracy affected by multiple factors, including the selection of design and simulation of model parameters, and so on. With the default parameters for the solution of basically meet the requirements of most of the performance of system simulation and emulation accuracy. However, for some simulation problems, if you try a different solution, or adjust the simulation parameters, simulation results can be better. Further, if to take into account the simulation object information, if it in the solution, then the simulation results will be greatly improved.If simulation is slow for a variety of reasons, ①Matlab in the simulation model of function modules. In each time step simulation requires calling Matlab interpreter, thus slowing down simulation speed. When a simulation in the structure, to make use of internal function modules or using arithmetic module. ②simulation model contains m s-function for the file. Same as repeatedly calling Matlab interpreter while slowing down simulation speed. S functions into subsystems or can be converted to s-function of the C-mex file. ③have a memory module in the simulation model. Use memory module makes changing solution in order to order reset to 1 for each simulation, thus slowing down simulation speed. ④When multi-sampling rate system simulation, between different sample rates does not satisfy the multiple relationship between each other, resulting in simulation solution when you need to adopt steps small enough to fit different sampling rate requirements, thus slowing down the speed of simulation. ⑤algebraic loop in the simulation model. Solution of algebraic loops are calculated at each time step of the iteration, so greatly impact simulation performance. In the same type of reasons there are many, is not going to elaborate here.Improvement of simulation accuracy, first check the simulation of the reasonable time period, reduce the relative or absolute accuracy after setting the simulation again, comparing the differences. If the result makes little difference, can verify that the basic simulation methods and results are correct. If simulation just start from the basic motion behaviors, can reduce the simulation step size to ensure that simulation is not out of the basic movement. If the simulation on the effective period of instability, probe into the possible causes and treatment methods are as follows: ①the object itself is not a stable system. ②can swap calculation. If the simulation result is not accurate, may for the following reasons: ①for those close to zero value of the model State, possibly due to set absolute accuracy is too large, resulting in a State of zero values near the neighborhood of simulation step is too small. Can reduce the absolute accuracy of the set value, or a single integrator in the dialog box to adjust the status. ②If this effect is not significant, consider reducing the relative accuracy of parameters setting, so that errors reduce to an acceptable error, reduce the simulation step size and use more simulation steps to resolve.。

matlab yalmip gurobi 编程指导 -回复

matlab yalmip gurobi 编程指导 -回复

matlab yalmip gurobi 编程指导-回复Matlab, Yalmip, and Gurobi Programming Guidance: Step by StepIntroduction:In this article, we will provide a step-by-step guide to programming in MATLAB using the YALMIP modeling language and the Gurobi optimization solver. This comprehensive guide will cover essential aspects of the MATLAB environment, explain how to install and set up YALMIP and Gurobi, and provide examples to help you understand the process better.Section 1: MATLAB Basics (250 words)Matlab is a numerical programming language that offers a wide range of functions, comprehensive toolboxes, and an interactive environment for data analysis, modeling, and simulation. To get started, you need to have MATLAB installed on your computer. Once installed, launch MATLAB, and you will be greeted with the MATLAB Command Window.Section 2: Installing YALMIP (250 words)YALMIP is a MATLAB-based modeling language for optimization problems. It allows you to express optimization problems in anatural way using MATLAB syntax. To install YALMIP, follow these steps:1. Download the YALMIP package from the official website.2. Extract the contents of the downloaded file to a directory of your choice.3. Add the path to the extracted directory to MATLAB's search path using the "addpath" command.Section 3: Setting up Gurobi (250 words)Gurobi is one of the leading optimization solvers available, known for its efficiency in solving large-scale mathematical programming problems. Here's how you can set up Gurobi:1. Download and install the Gurobi Optimizer binary for your operating system from the official Gurobi website.2. Once installed, obtain a license by following the instructions provided.3. Set up the Gurobi MATLAB interface by running the"gurobi_setup.m" script provided with the Gurobi installation.Section 4: Using YALMIP and Gurobi (750 words)Now that you have MATLAB, YALMIP, and Gurobi installed and set up, let's dive into some examples of how you can use themtogether to solve optimization problems. We will demonstrate the process using a simple linear programming example.Step 1: Define the decision variables and objective function (150 words)Start by defining your decision variables using MATLAB syntax. For example, to define a scalar variable 'x', you can use the command "x = sdpvar(1,1);". Next, define your objective function using the decision variables. For instance, "Objective = 3*x + 2;".Step 2: Set up constraints (150 words)Define the constraints of your optimization problem using MATLAB syntax. For example, if you have the constraint "2*x <= 10", you can express it as "Constraint = x <= 5;".Step 3: Set up the optimization problem (150 words)Now that you have defined your decision variables, objective function, and constraints, you can set up the optimization problem using the YALMIP syntax. For example, "OptimizationProblem = optimize(Constraint, Objective);".Step 4: Solve the optimization problem using Gurobi (150 words)To solve the optimization problem, you need to call the Gurobi solver. Use the command "optimize(OptimizationProblem, [], options);" to solve the problem. Here, 'options' can be customized to modify the solver's behavior.Step 5: Retrieve and interpret the solution (150 words)After the optimization problem has been solved, you can retrieve and interpret the solution using MATLAB syntax. For example, use "value(x)" to retrieve the value of decision variable 'x'. You can also obtain the optimal objective value using "value(Objective)".Conclusion (100 words)In conclusion, MATLAB, YALMIP, and Gurobi provide a powerful and user-friendly environment for formulating and solving optimization problems. By following this step-by-step guide, you should now have a good understanding of how to set up and use these tools together to solve optimization problems in MATLAB. Remember to explore the extensive documentation available for MATLAB, YALMIP, and Gurobi to further enhance your programming skills in this domain. Happy coding!。

MATLAB求解数学线性问题

MATLAB求解数学线性问题
ydx=(-(2*x-2)*exp(-x^2-y^2-x*y)-(x^2-2*x)*(-2*x-y)*exp(x^2-y^2-x*y))/(x^2-2*x)/(-2*y-x)/exp(-x^2-y^2-x*y)
2013-7-17 黄建华制作 23
4.1.3导数和微分

复合函数求导 例4.1.12 已知:
8
4.1.1符号方程的求解
首先建立函数文件fun.m并保存在默认路径下:
function y=fun(x)
y=[x(1)-0.5*sin(x(1))-0.3*cos(x(2)), ... x(2)- 0.5*cos(x(1))+0.3*sin(x(2))];
然后运行命令: >> clear;x0=[0.1,0.1];
2013-7-17 黄建华制作 21
4.1.3导数和微分
化简一下: 命令: >> zxzy1=simple(zxzy) zxzy1 =exp(-x^2-y^2-x*y)*(-4*x*y-3*x^2+4*y+4*x +5*x^3*y+2*x^4+2*x^2*y^2-10*x^2*y-4*x^3-4*x*y^2)
2013-7-17
黄建华制作
7
4.1.1符号方程的求解
例4.1.4
求解方程组:
x1 0.5 sin x1 0.3 cos x 2 0 x 2 0.5 cos x1 0.3 sin x 2 0
x0=[x(1),x(2)]=[0.1,0.1]
2013-7-17
黄建华制作
黄建华制作 1
4.1.1符号方程的求解
主要内容

线性方程

凸优化分析 -导论 斯坦福大学电子工程系必修课程

凸优化分析 -导论 斯坦福大学电子工程系必修课程

exceptions: certain problem classes can be solved efficiently and reliably • least-squares problems • linear programming problems • convex optimization problems
using convex optimization • often difficult to recognize • many tricks for transforming problems into convex form • surprisingly many problems can be solved via convex optimization
Introduction 1–6
i = 1, . . . , m
Convex optimization problem
minimize f0(x) subject to fi(x) ≤ bi,
i = 1, . . . , m
• objective and constraint functions are convex: fi(αx + βy) ≤ αfi(x) + βfi(y) if α + β = 1, α ≥ 0, β ≥ 0 • includes least-squares problems and linear programs as special cases
Introduction
1–12
Course goals and topics
goals 1. recognize/formulate problems (such as the illumination problem) as convex optimization problems 2. develop code for problems of moderate size (1000 lamps, 5000 patches) 3. characterize optimal solution (optimal power distribution), give limits of performance, etc. topics 1. convex sets, functions, optimization problems 2. examples and applications 3. algorithms

MatLab考试题题库(必做题)(带答案)

MatLab考试题题库(必做题)(带答案)

MatLab考试题题库(必做题)(带答案)一,1.请登陆美国 MathWorks 公司的网站 (),查看看现在大概有多少本 MATLAB-based books (以 MATLAB 为基本软件,来说明各个专业领域的教科书或工具书)。

哪一个领域的 MATLAB-based books 最多?中文书共有几本?答:1612本,数学方面的最多,中文书共有37本。

2.请在 MATLAB中直接输入下列常数,看它们的值是多少:a.ib.jc.epsd.infe.nanf.pig.realmaxh.realmin依次解为:ans = 0 + 1.0000i ans = 0 + 1.0000i ans =2.2204e-016 ans =Inf ans = NaN ans =3.1416 ans =1.7977e+308 ans =2.2251e-3083.试写一函数 regPolygon(n),其功能为画出一个圆心在 (0, 0)、半径为 1 的圆,并在圆内画出一个内接正 n 边形,其中一顶点位于 (0, 1)。

例如 regPolygon(8) 可以画出如下之正八边型:解:新建regPolygon.m文件如下:function y=regPolyfon(n)n=8;%要画的n边形R=1; %圆的半径t=0:0.01:2*pi;x=R*cos(t);y=R*sin(t);m=linspace(pi/2,5/2*pi,n+1);xz=R*cos(m);yz=R*sin(m);hold onplot(x,y,xz,yz);axis 'equal';4.一条参数式的曲线可由下列方程式表示:x = sin(t), y = 1 - cos(t) + t/10当 t 由 0 变化到 4*pi 时,请写一个 MATLAB 的脚本 plotParam.m,画出此曲线在 XY 平面的轨迹。

解:新建plotParam.m :t = linspace(0, 4*pi);x = sin(t);y = 1-cos(t)+t/10;plot(x, y, '-o'); -1-0.8-0.6-0.4-0.200.20.40.60.8100.511.522.535. 当一个小圆轮沿着一条曲线行进时,轮缘任一点的轨迹就会产生变化丰富的摆线。

如何在Matlab中进行线性规划问题求解

如何在Matlab中进行线性规划问题求解

如何在Matlab中进行线性规划问题求解线性规划(Linear Programming,LP)是数学规划的一个重要分支,其能够高效地解决许多实际问题。

在工业、运输、金融等领域中,线性规划的应用十分广泛。

而Matlab作为一种功能强大的数学软件,也提供了许多工具和函数用于线性规划问题的求解。

本文将介绍在Matlab中进行线性规划问题求解的基本步骤和常用函数。

一、线性规划概述线性规划是一种寻找线性目标函数在线性约束条件下的最优解的方法。

通常情况下,线性规划问题可以表示为:max/min z = c^T * xsubject to A * x <= bx >=0其中,c和x是n维向量,A是m×n的矩阵,b是m维向量。

目标是求解向量x的取值,使得目标函数c^T * x在满足约束条件A * x <= b和x >=0的前提下,取得最大(或最小)值z。

二、Matlab中线性规划求解函数Matlab中提供了多个函数用于线性规划问题的求解,其中最常用的是“linprog”函数。

linprog函数的基本语法如下所示:[x, fval, exitflag, output] = linprog(f, A, b, Aeq, beq, lb, ub, options)其中,参数f是目标函数的系数向量,A和b是不等式约束的矩阵和右侧向量,Aeq和beq是等式约束的矩阵和右侧向量,lb和ub分别是变量的下界和上界向量,options是优化选项。

三、解决实际问题的例子假设有一家电子公司,为了提高利润,决定如何分配生产资源。

公司生产三种产品A、B、C,每种产品所需的生产时间分别为5小时、10小时和15小时。

已知公司每周的生产时间为80小时,每单位产品的利润分别为5、8和10。

现在问题是如何分配生产时间,使得总利润最大化。

首先,我们需要确定目标函数和约束条件。

根据题意,我们可以将目标函数设置为z = 5*x(1) + 8*x(2) + 10*x(3),其中x(1)、x(2)和x(3)分别表示产品A、B、C的生产数量。

MATLAB英文翻译

MATLAB英文翻译

Teaching Electronics with MATLABJohn Okyere AttiaDepartment of Electrical EngineeringPrairie View A&M UniversityP.0. Box 397, Prairie View, Texas 77446 Abstract:MATLAB is a numeric computation software for engineering and scientific calculations.MATLAB is being used to teach circuit theory,filter design,random processes,control system and communication theory.MATLABmatrix functions are shown to be versatile in doing analysis of data obtained from electronics experiments.The graphical features of MATLAB are especially useful for display of frequency response of ampl$ers and illustrating the principles and concepts of semiconductor physics.17ze interactive programming and versatile graphics of MATLAB is especially effective in exploring some of the characteristics of devices and electronic circuits.IntroductionThe electrical engineering program at Prairie View A&M University has integrated computer-aided engineering (CAE) and computer-aided design (CAD) packages in its curriculum.Two of the popular software packages that is used in the department are MATLAB and PSPICE. The aims of incorporating the packages into the curriculum are (i) to enhance the theoretical understanding of engineering principles and concepts, (ii) to allow students to solve fairly complex problems that would otherwise be impossible without CAE and CAD packages.In addition, we want to introduce our students to software programs that they will use after graduation.Whereas, SPICE is de facto university and industry standard for analog circuit simulation,and it is indispensable for simulating medium-scale and very large-scale integrated circuits, there are cases where the use of MATLAB supplements the capabilities of SPICE.This paper describes some areas in electronics where MATLAB have been used to teach electronics to undergraduate electrical engineering students. MatlabMATLAB is a numeric computation software for engineering and scientific calculations. MATLAB is primarily a tool for matrix computations[l].MATLAB is a high level language whose basic data type is a matrix that does not require dimensioning.There is no compilation and linking of programs as it is normally done in other high level languages,such as C or FORTRAN.In MATLAB, all computations are done in complex valued double precision arithmetic to guarantee high accuracy.MATLAB has a rich set of plotting capabilities.The graphics are integrated into MATLAB.Since MATLAB is also a programming environment, a user can extend the functional capabilities of MATLAB by writing new modules.MATLAB has a large collection of toolboxes for variety of applications. A toolbox consists of functions that can be used to perform some computations in the toolbox domain. Some examples of MATLAB toolboxes are: signal processing, image processing, neural network, control system, statistics,symbolic mathematics,optimization and system identification.MATLAB is being used to teach filter design [2], random processes [3], control systems [4], communication theory [5],and circuit analysis[6,7].Circuit Simulator —SPICESPICE is one of the most successful circuit simulation programs. Its widespread usage attests to the applicability of the program to large variety of circuit simulation problems. SPICE utilizes modified nodal analysis approach. It can be used for non-linear dc,non-linear transient and linear ac analysis problems.It can also be used to perform noise analysis,temperature analysis, Monte-Carlo analysis. One of the advantages of SPICE is its inclusion of device models for active devices such as dicde, BJT, JFET, and MOSFBT[8]Electronic Courses at Prairie View A&M UniversityIn the dcpartment of Electrical Engineering at Prairie View A&M University,there are three required electronics courses:Physical Electronics, Electronics I and Electronics II.In Physical Electronics, we cover the basic laws of electron motion,behavior of charges in solids, semiconductor device physics, device behavior in DC circuits.In Electronics I, the following topics are discussed: operational amplifier, diodes, field effect transistors, bipolar junction transistors, analysis and design of linear ampaers, biasing, small and large signal behavior.The following topics are covered in Electronics II:Design and analysis of multistage amplifiers,difference amplifiers,fkequency response of amplifiers,feedbackconcepts, analysis and design using discrete and integratedcircuits.In addition,to the three course, the department has a course, Electronics Laboratory, which covers topics in Electronics I and II.Examples of the Use of MATLAB in Electronics1.Frequency Response of umpliJers &filtersFor simple electronic circuits, the transfer function can be found.MATLAB can then be used to obtain the poles and zeros of the circuit.For example, for an electronic circuit with the transfer function011101111)(H a s a s a s a b s b s b s b s n n n n m m m m ++++++++=----The MATLAB function roots can be used to determine the roots of a polynomial.The poles and zeros of the circuit can be plotted using the MATLAB function zplane.The function polyvd is used for polynomial evaluation.The function freqs can easily be used to obtain the ftequency response. The versatile nature of MATLAB allows "what-?? analysis.In addition, the graphical features of MATLAB help students to learn the type of amplifier (direct-coupled,RC-coupled, tuned) or filter (lowpass, highpass, bandreject, bandpass) obtained Erom various transfer functions and circuits.2.Analysis of Simple Diode CircuitsBoth MATLAB and SPICE can be used to analyze simple diode circuits. MATLAB can be used to obtain the diode current and voltage using iterative technique [9]. In addition,for rectifiers with filter capacitor, MATLAB can be used to solve the transcendental equations needed to obtain the turn-on, turn-off time and hence, the conduction time of the diode. For battery charging circuit[9], the fraction of time the diode conducts and the peak value of diode current can be examined under different conditions using MATLAB.3.Analysis of Electronics Laboratory DataData obtained from electronic devices can be analyzed using MATLAEL In one of the electronics laboratory sessions, the students obtain the corresponding values of the current passing through and voltage across a diode.They use MATLAB (i) to plot the semiconductor diode i-v characteristics, (ii) to determine the reverse saturation current and diode empirical constant. The MATLAB functions that have been found useful in electronic data analysis are: diff,colon operator, save, load.4.Illustrating semiconductor device concepts and device characterizationWe are using MATLAB to determine the electron concentration in bulk silicon as a function of temperature, to obtain the majority and minority carriers in a semiconductor device at various doping concentrations,to describe the effect of doping concentration on both electron and hole mobilities. For pn junctions, MATLAB is very useful in illustrating the depletion capacitance vs. junction potential;and the breakdown voltage vs.doping concentration.The interactivenature of MAW, its immediate graphing facilities and built-in functions are especially useful in reinforcement of student understanding of semiconductor fundamentals. Comparison of MATLAB Electronics and SPICE for Both MATLAB and SPICE are currently being used for teaching electronics at Prairie View A&M University. There are other universities that are using both MATLAB and SPICE in their electrical engineering curriculum [l0].SPICE can simulate small to very large electronic circuits. MATLAB is more suited to analyzing small circuits.SPICE package include device models.Device models are not part of MATLAB.Poles and zeros can easily be obtained using MATLAB. At present, SPICE does not have the facility for determining poles and zeros of circuits.The computational and graphical nature of MATLAB are well-suited for describing the characteristics of extrinsic and intrinsic semiconductors. SPICE program was not written to describe the characteristics of semiconductor materials.Whereas SPICE can display the i- v characteristics of pn junctions,the depletion capacitance as a function of junction potential, the breakdown voltage of pn junction with respect to doping concentration,and other junction Characteristics can be handled by more easily by MATLAB than by SPICE.Table 1 summarizes the strengths and limitations of the two packages with respect to teaching electronics. Features SPICE MATLABType of Circuits fo Analysis small to veIy largecircuitssmall circuitsFrequency Response yes yesInclusion of DeviceModel in SoftwarePackageyes noDetermination and plotof poles and zerosno yesBulk SemiconductorCharacteristicsno yespn junctioncharacteristics -excluding I-vcharacteristicsno yesReaction from StudentsMATLAB has been used in our program for the past four years.The students find MATLAB easy to learn. This can be attributed to its extensive tutorials,on-line help, interactive nature and versatile graphics.The response of students who use MATLAB in electronics and other electrical engineering courses has been positive. Students remark that (i) MATLAB reinforces their understanding of theoretical principles and (ii) increases their interest in the subject matter.ConclusionsAreas in electronics where MATLAB can be used to teach electronics principles and concepts to electrical engineering students are discussed.MATLAB has been used to examine the frequency response of mplifias and filters. The versatile nature of MATLAB allows "what-if'' analysis that can be used to strengthen students understanding of electronics.MATLAB is useful in analyzing data obtained fiom electronics laboratory experiments.In addition, it has been found that theinteractive nature of MATLAB and its immediate graphing facilities are especiallyuseful in enhancing the understanding of concepts and principles of semiconductor fundamentals. Furthermore, MATLAB and SPICE are compared with respect to teaching electronicsReferences[1] Etter, D.M. "Engineering Problem Solving using MAW" Prentice Hall, 1993.[2] Burms, C.S. "Teaching Filter Design using MAIZAB', ICASSP, V ol. 1, pp. 20 - 23, 1993.[3] Kirlin, R.L. and Hedstrom, B.A. "A Computer- Oriented Random Processes Course for a Mix of Graduates and Undergraduates" ICASSP, V ol. 1, pp. 24 - 27,1993.[4] Ogata, K. "Solving Control Engineering Problems with MAIZAB" Prentice Hall, 1994.[5] Attia, J.O. "Teaching Communication %oly Using MAZZAB" 1995 Engineering and Architecture Symposium, Prairie View A&M University, Prairie View, Texas, pp. 435 -440, Jan.30 - 31,1995.[6] Gottling, J.G. "Matrix Analysis of Circuits Using MAIZAB",Prentice Hall, 1995.[7] Attia, J.O. "Teaching AC Circuit Analysis with MAZAB", Proc. of Frontiers in Education, 25th Annual Conference, Atlanta, Georgia, pp. 2c6.9 - 2~6.12, 1995.[8] Vladimirescu, A. "% Spice Book " John Wiley and Sons, Inc, 1994.[9] Sedra, AS. and Smith, K.C. "Microelectronic Circuits 'I,Saunders College Publishing, 1991.[10] Azemi, A. and Yaz, E.E. "Pspice and MAW in Undergraduate and Graduate Electrical Engineering ",Proc. of Frontiers in Education, 24th Annual Conference, pp. 456 - 459,1994.译文:教学电子,用MATLAB摘要:matlab是一种数值计算软件,matlab环境工程与科学计算存在用于教育、滤波器设计电路理论、随机过程,控制系统和通信理论.matlab矩阵函数的结果做分析的多功能电子实验得到的数据。

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What to do when some of the
variables are missing ?
For example, suppose there are no lower bounds on the variables. In this case define l to be the empty set using the MATLAB command:
Use MATLAB to solve linear programs
LI Xiao-lei
MATLAB format for linear programs
MATLAB uses the following format for
linear prog. t. Ax ≤ b
>> l = []; Do this and resolve the LP by calling the linprog
command. You should see: Optimization terminated successfully. x= 0.6667 -0.3333 0.6667
What to do when some of the variables are missing ?
Aeq = beq
(1)
x≥ l
x≤u
Command format
A linear program in the format of equation (1) is solved using the command:
x = linprog(f ,A, b, Aeq, beq, l, u)
Simple example
Solve the linear program using MATLAB:
>> x = linprog(f,A,b,Aeq,beq,l,u) And you should see the following: Optimization terminated successfully. x= 0.5000 0.0000 0.5000
Similarly define other matrices to be empty matrices if they do not appear in the problem.
For example, if there are no equality constraints, define Aeq and beq as empty sets, i.e.
>> Aeq = []; >> beq = []; So this and resolve the LP by calling linprog. You should see: Optimization terminated successfully. x= 0.0000 1.0000 1.0000
Input the variables into MATLAB:
>> f = -[4;2;1]; >> A = [2 1 0;1 0 2]; >> b = [1;2]; >> Aeq = [1 1 1]; >> beq = [1]; >> l = [0;0;0]; >> u = [1;1;2];
Simple example
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