ivan@155: clear
ivan@155: IT = 1000; % Number of iterations
ivan@155: R = 3:7; % Sparsity of the signals
ivan@155: SN = 5; % Number of trials
ivan@155: M = 20; % Signal space dimension
ivan@155: N = 40; % Ambient space dimension
ivan@155: L = 32*N; % Number of training signals
ivan@155: 
ivan@155: ParamGen(M,N,L,R,SN) % Generating generic problems
ivan@155: 
ivan@155: %%%% Dictionary recovery algorithms
ivan@155: for sn = 1:SN    
ivan@155:     for r = R
ivan@155:         mmdlcn_exactRec_demo(IT,r,sn,'un')
ivan@155:         mapcn_exactRec_demo(IT,r,sn,'bn')
ivan@155:         ksvd_exactRec_demo(IT,r,sn)
ivan@155:         modcn_exactRec_demo(IT,r,sn)
ivan@155:     end
ivan@155: end
ivan@155: %%%%%%%
ivan@155: Tre = .99;
ivan@155: for k = R
ivan@155:     for i=1:SN
ivan@155:         load(['RDLl1',num2str(M),'t',num2str(IT),'ikiun',num2str(k),'v1d',num2str(i),'.mat'])
ivan@155:         nrRDLu(i,k-R(1)+1) = sum(max(abs((Phid'*Phi)))>=Tre);
ivan@155:         %%%%%%
ivan@155:         load(['MAPl1',num2str(M),'t',num2str(IT),'ikiun',num2str(k),'v1d',num2str(i),'.mat'])
ivan@155:         nrMAP(i,k-R(1)+1) = sum(max(abs((Phid'*Phi)))>=Tre);        
ivan@155:         %%%%%%
ivan@155:         load(['KSVDl1',num2str(M),'t',num2str(IT),'ikiun',num2str(k),'v1d',num2str(i),'.mat'])
ivan@155:         nrKSVD(i,k-R(1)+1) = sum(max(abs((Phid'*Phi)))>=Tre);
ivan@155:         %%%%%%
ivan@155:         load(['MODl1',num2str(M),'t',num2str(IT),'ikiun',num2str(k),'v1d',num2str(i),'.mat'])
ivan@155:         nrMOD(i,k-R(1)+1) = sum(max(abs((Phid'*Phi)))>=Tre);
ivan@155:     end
ivan@155: end
ivan@155: clf
ivan@155: errorbar(R+.01,10*mean(nrRDLu,1)/4,std(nrRDLu,0,1),'k-.')
ivan@155: hold on
ivan@155: errorbar(R-.01,10*mean(nrKSVD,1)/4,std(nrKSVD,0,1),'r*-')
ivan@155: errorbar(R+.01,10*mean(nrMOD,1)/4,std(nrMOD,0,1),'b-v')
ivan@155: errorbar(R-.01,10*mean(nrMAP,1)/4,std(nrMAP,0,1),'b-^')
ivan@155: axis([2.5 7.5 15 105]);
ivan@155: title('Constrained column-norm dictionaries')
ivan@155: xlabel('Sparsity (# of non-zero elements in each coefficient vector)')
ivan@155: ylabel(['Average percents of exact recovery',sprintf('\n'),'after ',num2str(IT),' iterations'])
ivan@155: grid on
ivan@155: legend('MM Unit norm','K-SVD','MOD','MAPbased-DL');
ivan@155: axis([2.8 7.2 -5 105])