relnwt_test.m

该代码为盲源分离中的相对牛顿法

%  relnwt_test.m  - TEST of relnewton.m  


%%%%%%%%% Generate sparse  data %%%%%%%%
N=3;
T=1000;
A=rand(N);
S=sprandn(N,T,0.5);
X=A*S;

%%%%%% Setup the parameters

lam=1e-1; % parameter of smoothing of the absolute value function
niter=100
normg_tol=1e-10;
%method='relnwt';  
method= 'fastnwt'; 


%%%%%%% Separate with the relative NEWTON %%%%%%%%
W=relnewton(X,lam,niter,normg_tol,method)

%%%%%%%% COMPUTE QUALITY OF SEPARATION
WA=W*A
ISR=max(sep_quality(WA))


return



%%%%%%%%% Generate the uniformly distributed sources %%%%%%%%
S= rand(N,T) - 0.5;
X=A*S;


%%%%%%% Separate with the relative NEWTON %%%%%%%%

lam=-6;    % use nonlinearity s^6   
W=relnewton(X,lam)

%%%%%%%% COMPUTE QUALITY OF SEPARATION
WA=W*A
ISR=max(sep_quality(WA))