迭代门限方法的MATLAB实现

% test1 % Test the performance of: % iterative hard threshold; % iterative hard threshold K; % iterative soft threshold clear all close all clc k=100; lamda=0.09; Lamda=0.01; n=500; m=300; times=200; x=SparseSignal(n,k,1); x=x/norm(x); % normlization phi=SensingMatrix(m,n,1); tau=1.9/norm(phi)^2; tic y=phi*x; [xhat1,error1,I1]=IHT_K(phi,y,x,k,tau,times); [xhat2,error2,I2]=IHT(phi,y,x,lamda,tau,times); [xhat3,error3,I3]=IST(phi,y,x,Lamda,tau,times); toc figure(1) subplot(2,2,1) stem(x,'.') xlabel('Orignal Signal') subplot(2,2,2) stem(real(xhat1),'.') xlabel('Hard Threshold K') subplot(2,2,3) stem(real(xhat2),'.') xlabel('Hard Threshold') subplot(2,2,4) stem(real(xhat3),'.') xlabel('Soft Threshold') figure(2) subplot(2,2,1) stem(x) xlabel('Orignal Signal') subplot(2,2,2) plot(error1) xlabel('Hard Threshold K') subplot(2,2,3) plot(error2) xlabel('Hard Threshold') subplot(2,2,4) plot(error3) xlabel('Soft Threshold') figure(3) subplot(2,2,1) stem(x) xlabel('Orignal Signal') subplot(2,2,2) plot(x,real(xhat1),'*'); xlabel('Hard Threshold K') subplot(2,2,3) plot(x,real(xhat2),'*'); xlabel('Hard Threshold') subplot(2,2,4) plot(x,real(xhat3),'*'); xlabel('Soft Threshold')