LDA人脸识别地matlab程序

实用文案LDA人脸识别的matlab 程序以下是LDA的m文件函数：你稍稍改改就能用了！function[eigvector,eigvalue,elapse]=LDA(gnd,options,data)LDA:LinearDiscriminantAnalysis% [eigvector,eigvalue]=LDA(gnd,options,data)%% Input:% data -Datamatrix.Eachrowvectoroffeaisadatapoint.% gnd -Colunmvectorofthelabelinformationforeach% datapoint.% options-StructvalueinMatlab.Thefieldsinoptions% thatcanbeset:%% Regu - 1:regularizedsolution,% a*=argmax(a'X'WXa)/(a'X'Xa+ReguAlpha*I)标准文档实用文案%0:solvethesinularityproblembySVD%Default:0%%ReguAlpha-Theregularizationparameter.Valid%whenRegu==1.Defaultvalueis0.1.%%ReguType-'Ridge':Tikhonovregularization%'Custom':Userprovided%regularizationmatrix%Default:'Ridge'%regularizerR-(nFeaxnFea)regularization%matrixwhichshouldbeprovided%ifReguTypeis'Custom'.nFeais标准文档实用文案% thefeaturenumberofdata% matrix% Fisherface - 1:Fisherfaceapproach% PCARatio=nSmp-nClass% Default:0%% PCARatio - Thepercentageofprincipal% componentkeptinthePCA% step.Thepercentageis% calculatedbasedonthe% eigenvalue.Defaultis1% (100%,allthenon-zero% eigenvalueswillbekept.% IfPCARatio>1,thePCAstep% willkeepexactlyPCARatioprinciple标准文档实用文案%components(doesnotexceedthe%exactnumberofnon-zerocomponents).%%%Output:%eigvector-Eachcolumnisanembeddingfunction,foranew%datapoint(rowvector)x,y=x*eigvector%willbetheembeddingresultofx.%eigvalue-ThesortedeigvalueofLDAeigen-problem.%elapse-Timespentondifferentsteps%Examples:% fea=rand(50,70);% gnd=[ones(10,1);ones(15,1)*2;ones(10,1)*3;ones(15,1)*4];% options=[];% options.Fisherface=1;% [eigvector,eigvalue]=LDA(gnd,options,fea);% Y=fea*eigvector;标准文档实用文案%%SeealsoLPP,constructW,LGE%Reference:% P.N.Belhumeur,J.P.Hespanha,andD.J.Kriegman, 揈igenfacesvs.fisherfaces:recognitionusingclassspecificlinear% projection, ? IEEETransactionsonPatternAnalysisandMachineIntelligence,vol.19,no.7,pp.711-720,July1997.DengCai,XiaofeiHe,YuxiaoHu,JiaweiHan,andThomasHuang,"LearningaSpatiallySmoothSubspaceforFaceRecognition",CVPR'2007DengCai,XiaofeiHe,JiaweiHan,"SRDA:AnEfficientAlgorithmforLargeScaleDiscriminantAnalysis",IEEETransactionsonKnowledgeandDataEngineering,2007.%标准文档实用文案version2.1--June/2007version2.0--May/2007version1.1--Feb/2006version1.0--April/2004if~exist('data','var')globaldata;endif(~exist('options','var'))options=[];endif~isfield(options,'Regu')|~options.RegubPCA=1;if~isfield(options,'PCARatio')options.PCARatio=1;endelse标准文档实用文案bPCA=0;if~isfield(options,'ReguType')options.ReguType='Ridge';endif~isfield(options,'ReguAlpha')options.ReguAlpha=0.1;endendtmp_T=cputime;======Initialization[nSmp,nFea]=size(data);iflength(gnd)~=nSmperror('gndanddatamismatch!');endclassLabel=unique(gnd);nClass=length(classLabel);Dim=nClass-1;ifbPCA&isfield(options,'Fisherface')&options.Fisherface标准文档实用文案options.PCARatio=nSmp-nClass;endifissparse(data)data=full(data);endsampleMean=mean(data,1);data=(data-repmat(sampleMean,nSmp,1));bChol=0;ifbPCA&(nSmp>nFea+1)&(options.PCARatio>=1)DPrime=data'*data;DPrime=max(DPrime,DPrime');[R,p]=chol(DPrime);ifp==0bPCA=0;bChol=1;end标准文档实用文案end%======================================SVD%======================================ifbPCAifnSmp>nFeaddata=data'*data;ddata=max(ddata,ddata');[eigvector_PCA,eigvalue_PCA]=eig(ddata);eigvalue_PCA=diag(eigvalue_PCA);clearddata;maxEigValue=max(abs(eigvalue_PCA));eigIdx=find(eigvalue_PCA/maxEigValue<1e-12);eigvalue_PCA(eigIdx)=[];eigvector_PCA(:,eigIdx)=[];[junk,index]=sort(-eigvalue_PCA);eigvalue_PCA=eigvalue_PCA(index);标准文档实用文案eigvector_PCA=eigvector_PCA(:,index);%=======================================ifoptions.PCARatio>1idx=options.PCARatio;ifidx<length(eigvalue_PCA)eigvalue_PCA=eigvalue_PCA(1:idx);eigvector_PCA=eigvector_PCA(:,1:idx);endelseifoptions.PCARatio<1sumEig=sum(eigvalue_PCA);sumEig=sumEig*options.PCARatio;sumNow=0;foridx=1:length(eigvalue_PCA)sumNow=sumNow+eigvalue_PCA(idx);ifsumNow>=sumEigbreak;endendeigvalue_PCA=eigvalue_PCA(1:idx);eigvector_PCA=eigvector_PCA(:,1:idx);end标准文档实用文案%=======================================eigvalue_PCA=eigvalue_PCA.^-.5;data=(data*eigvector_PCA).*repmat(eigvalue_PCA',nSmp,1);elseddata=data*data';ddata=max(ddata,ddata');[eigvector,eigvalue_PCA]=eig(ddata);eigvalue_PCA=diag(eigvalue_PCA);clearddata;maxEigValue=max(eigvalue_PCA);eigIdx=find(eigvalue_PCA/maxEigValue<1e-12);eigvalue_PCA(eigIdx)=[];eigvector(:,eigIdx)=[];[junk,index]=sort(-eigvalue_PCA);eigvalue_PCA=eigvalue_PCA(index);eigvector=eigvector(:,index);%=======================================标准文档实用文案ifoptions.PCARatio>1idx=options.PCARatio;ifidx<length(eigvalue_PCA)eigvalue_PCA=eigvalue_PCA(1:idx);eigvector=eigvector(:,1:idx);endelseifoptions.PCARatio<1sumEig=sum(eigvalue_PCA);sumEig=sumEig*options.PCARatio;sumNow=0;foridx=1:length(eigvalue_PCA)sumNow=sumNow+eigvalue_PCA(idx);ifsumNow>=sumEigbreak;endendeigvalue_PCA=eigvalue_PCA(1:idx);eigvector=eigvector(:,1:idx);end%=======================================标准文档实用文案eigvalue_PCA=eigvalue_PCA.^-.5;eigvector_PCA=(data'*eigvector).*repmat(eigvalue_PCA',nFea,1);data=eigvector;cleareigvector;endelseif~bCholDPrime=data'*data;% options.ReguAlpha=nSmp*options.ReguAlpha;switchlower(options.ReguType)case{lower('Ridge')}fori=1:size(DPrime,1)DPrime(i,i)=DPrime(i,i)+options.ReguAlpha;endcase{lower('Tensor')}DPrime=DPrime+case{lower('Custom')}标准文档实用文案DPrime=DPrime+otherwiseerror('ReguTypedoesnotexist!');endDPrime=max(DPrime,DPrime');endend[nSmp,nFea]=size(data);Hb=zeros(nClass,nFea);fori=1:nClass,index=find(gnd==classLabel(i));classMean=mean(data(index,:),1);Hb(i,:)=sqrt(length(index))*classMean;endelapse.timeW=0;elapse.timePCA=cputime-tmp_T;标准文档实用文案tmp_T=cputime;ifbPCA[dumpVec,eigvalue,eigvector]=svd(Hb,'econ');eigvalue=diag(eigvalue);eigIdx=find(eigvalue<1e-3);eigvalue(eigIdx)=[];eigvector(:,eigIdx)=[];eigvalue=eigvalue.^2;eigvector=eigvector_PCA*(repmat(eigvalue_PCA,1,length(eigvalue)).*eigvector);elseWPrime=Hb'*Hb;WPrime=max(WPrime,WPrime');dimMatrix=size(WPrime,2);ifDim>dimMatrixDim=dimMatrix;标准文档实用文案endifisfield(options,'bEigs')ifoptions.bEigsbEigs=1;elsebEigs=0;endelseif(dimMatrix>1000&Dim<dimMatrix/10)|(dimMatrix>500&Dim<dimMatrix/20)|(dimMatrix>250&Dim