cov_matrix_norm.m

Fs=44100;
dr=dir('*.wav');
if length(dr)>0
    nm=[];
    for fc=1:length(dr)
        fln=dr(fc).name;
        lfln=length(fln);
        ns=fln(1:lfln-4);
        nm=[nm str2num(ns)];
    end
    [nms ind]=sort(nm);

    L=length(dr);
    ca=cell(L,1);
    lca=zeros(L,1);
    for fc=1:length(dr)
        [s1 Fs1]=wavread(dr(ind(fc)).name);
        s=resample(s1,2,1);
        ca{fc}=s;
        lca(fc)=length(s);
     
    end
    %soundsc(ca,44100);
    
end

Fs=Fs1*2;

% make equal length specters
%t01=0.1;
%n01=round(t01*Fs);
n01=4096;
n0=8000;
fab=cell(L,1);
for fc=1:L
    fca=fft(ca{fc}(n0:n0+n01-1));
    fabt=abs(fca(1:(n01/2)));
    fab{fc}=fabt/sum(fabt);
    
end



% covariation matrix:
cm=zeros(L,L);

for fc1=1:L
    fab1=fab{fc1};
    for fc2=1:L
        fab2=fab{fc2};
        cm(fc1,fc2)=sum(fab1.*fab2);
    end
end

cm0=cm;

n02=n01/2;


dg=zeros(L,1);
for fc=1:L
    dg(fc)=cm(fc,fc);
end
%plot(dg)
w=1./dg;


cm=zeros(L,L);

for fc1=1:L
    fab1=fab{fc1};
    for fc2=1:L
        fab2=fab{fc2};
        cm(fc1,fc2)=sum(fab1.*w(fc1).*fab2);
    end
end

% for fc1=1:L
%     for fc2=1:L
%         if cm(fc1,fc2)>0.8
%             cm(fc1,fc2)=1;
%         else
%             cm(fc1,fc2)=0.1*cm(fc1,fc2);
%         end
%     end
% end

imagesc(cm);
colorbar;