comparison DL/Majorization Minimization DL/ExactDicoRecovery/mapdl_cn.m @ 159:23763c5fbda5 danieleb

Merge

+% Maximum A Posteriori Estimation for Dictionary Learning
+% Y = input data (M X L matrix)
+% Phi = initial dictionary (M X N), e.g. random dictionary or first N data samples
+% lambda = regularization coefficient (||Phi*X-Y||_F)^2 + lambda*||X||_1
+% IT + number of iterations
+% res = dictionary constraint. 'un' = unit colomn norm, 'bn' = bounded colomn norm
+function [Phiout,X,ert] = mapdl_cn(Y,Phi,lambda,IT,res)
+maxIT = 1000;
+[PhiN,PhiM] = size(Phi);
+RR1 = PhiM;
+%%%%%%%%%%%%%%
+% [PhiM,L] = size(ud);
+[PhiN,L] = size(Y);
+X = ones(PhiM,L);
+for it = 1:IT
+    to = .1+svds(Phi,1);
+    [PhiN,PhiM] = size(Phi);
+    %%%%
+    eps = 3*10^-4;    
+    map = 1; % Projecting on the selected space (0=no,1=yes)
+    [X,l1err] = mm1(Phi,Y,X,to,lambda,maxIT,eps,map); %% Sparse approximation with Iterative Soft-thresholding
+    ert(it) = l1err;
+    %%%
+    eps = 10^-7;  
+    mu = 10^-4;
+    [Phi,X] = dict_update_MAP_cn(Phi,Y,X,mu,maxIT,eps,res);  
+end
+Phiout = Phi;