main.m

这是盲信号的代码 都已经通过编译了 做这方面的同仁可以参考一下 我觉得蛮惯用的

%*************** setup sources **********
format compact

%**** if you are mixing the sources yourself:

sources=readsounds(['man.wav';'wom.wav']); 


[N,P]=size(sources);                 % P=17408, N=2, for example
permute=randperm(P);                 % generate a permutation vector
s=sources(:,permute);                % time-scrambled inputs for stationarity

a=[1 2; 1 1];                         % mixing matrix, or:  a=rand(N);
x=a*s;                               % mix input signals (permuted)
mixes=a*sources;                

%**** if you are loading already-mixed sources:
%mixes=readsounds(['mix2';'mix1']);  % see "help readsounds"

%**** prewhite the data
mx=mean(mixes'); 
c=cov(mixes');
x=x-mx'*ones(1,P);                   % subtract means from mixes
wz=2*inv(sqrtm(c));                  % get decorrelating matrix
x=wz*x; 

%**** 
w=eye(N);                            % init. unmixing matrix, or w=rand(M,N);
M=size(w,2);                            % M=N usually
sweep=0; 
%oldw=w; 
%olddelta=ones(1,N*N);
Id=eye(M);
%************* this learns: "help sep" explains all 
 % only two sources,choose L=0.01; B=30;
L=0.01; B=30; sep   
 % more than two sources,choose L=0.001; B=30;
%L=0.001; B=30; sep   
% more than one hundred sources,choose L=0.01; B=30;
%L=0.0001; B=30; sep  % and so on

%for multiple sweeps:
%L=0.005; B=30; 
%for I=1:10000, sep; end;
%***************************************
mplot(sources);
xlabel('sources');
mixes=a*sources;       % make mixed sources
figure(2);
mplot(mixes);
xlabel('mixed signals');
%plot(mixes(1,:))       % plot the first one (if it is another signal)
uu=w*wz*mixes;            % make unmixed sources
%sound(uu(1,:))         % play the first one (if it is audio)
uu(1,:)=uu(1,:)/max(uu(1,:));
uu(2,:)=uu(2,:)/max(uu(2,:));
figure(3);
mplot(uu);
xlabel('unmix signals');