Ica盲源分离Matlab程序.docx

Ica盲源分离Matlab程序close all;clear all;i4=imread(1.jpg);i5=imread(2.jpg);i6=imread(2.png);i1=rgb2gray(i4);i2=rgb2gray(i5);i3=rgb2gray(i6);s1=reshape(i1,1,256*256);s2=reshape(i2,1,256*256);s3=reshape(i3,1,256*256);s=s1;s2;s3;sig=double(s);aorig=rand(size(sig,1);mixedsig=aorig*sig;ms1=reshape(mixedsig(1,:),256,256);ms2=reshape(mixedsig(2,:),256,256);ms3=reshape(mixedsig(3,:),256,256);figure;subplot(331),imshow(i1),subplot(332),imshow(i2),subplot(333),imshow(i3);subplot(334),imshow(uint8(ms1),subplot(335),imshow(uint8(ms2),subplot(336),imshow(uint8(ms3);% mixedsig=zeros(size(mixedsig);meanValue=mean(mixedsig);mixedsig=mixedsig-meanValue*ones(1,size(mixedsig,2);covarianceMatrix=cov(mixedsig,1);E,D=eig(covarianceMatrix);eigenvalues=flipud(sort(diag(D);whiteningMatrix=inv(sqrt(D)*E;dewhiteningMatrix=E*sqrt(D);whitesig=whiteningMatrix*mixedsig;X=whitesig;vectorSize,numSamples=size(X);B=zeros(vectorSize);numOFIC=vectorSize;for r=1:numOFIC i=1;maxNumIterations=100; w=rand(vectorSize,1)-.5; w=w/norm(w); while i=maxNumIterations+1 w=w-B*B*w; w=w/norm(w); w=(X*(X*w).3)/numSamples-3*w; w=w/norm(w); i=i+1; end A(:,r)=dewhiteningMatrix*w; W(r,:)=w*whiteningMatrix; B(:,r)=w;endicasig=W*mixedsig+(W*meanValue)*ones(1,numSamples);icasig=abs(50*icasig);a=reshape(icasig(1,:),256,256);b=reshape(icasig(2,:),256,256);c=reshape(icasig(3,:),256,256);subplot(337),im