Page 77 - Algorithm Collections for Digital Signal Processing Applications using MATLAB

2. Probability and Random Process 65

1.2 M-file for Independent Component Analysis

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icagv.m

%ICA WITH THREE COMPONENTS

close all
clear all
i=0:1/10:1000;
a=sin(0.1*pi*i);
a=a(1:1:10000);
a=meanvarnorm(a,0,1)
b=randn(1,10000);
b=meanvarnorm(b,0,1);
i=0:1/10:1000;
c=exp(0.001*pi*i);
c=meanvarnorm(c,0,1);
c=c(1:1:10000);
s1=0.9*a+0.6*b+0.6*c;
s1=meanvarnorm(s1,0,1);
s2=0.6*a+0.9*b+0.6*c;
s2=meanvarnorm(s2,0,1);
s3=0.6*a+0.6*b+0.9*c;
s3=meanvarnorm(s3,0,1);
figure
subplot(3,1,1)
plot(a);
subplot(3,1,2)
plot(b);
subplot(3,1,3)
plot(c);
figure
subplot(3,1,1)
plot(s1);
subplot(3,1,2)
plot(s2);
subplot(3,1,3)
plot(s3);
%ICA START
data1=[s1;s2;s3];
MEANMAT=repmat(mean(data1')',1,length(data1));