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Author: NeuroFan

MATLAB/AMP.m

@@ -0,0 +1,26 @@
+function xhat=AMP(y,H,landa,iterAMP,m,n)
+%% y is measurement vector; H is measurement matrix, iterAMP is number of iterations, m and n are matrix dimentions
+    r=y;
+    s=zeros(n,1);
+    sqM=sqrt(m);
+
+for t=1:iterAMP
+    
+    maxs=sort(abs(r),'descend');
+    sigma=mean(maxs(1:20));%norm(r)/sqM;    
+    g=H'*r;
+    s=s+g;
+    
+    %minOFmaxs=mean(maxs(1:10));
+    for i=1:n
+           s(i)=sign(s(i))*max(abs(s(i))-sigma,0);
+    end
+    %for i=1:n %thresholding
+     %   a=middle(i);
+      %  s(i)=sign(a)*max(abs(a)-sigma,0);
+    %end
+     b=sum(abs(s)>0)/m;
+     r=y-H*s+b.*r;
+end
+    xhat=s;
+end  

MATLAB/IHT_Mine.m

@@ -0,0 +1,16 @@
+function x=IHT_Mine(y,A,k,iteration)
+[M,N]=size(A);
+xnew=zeros(N,1);
+r=y-A*xnew;
+for i=1:iteration
+   g=A'*(r);
+   w=0.001;%(g'*g)/(g'*(A'*A)*g);
+   x=xnew+w*g;
+   [v,s]=sort(abs(x),'descend');
+   T=s(1:k);
+   xnew(:)=0; 
+   xnew(T)=x(T);
+   r=y-A*xnew;
+end
+x=xnew;
+end

MATLAB/OMP.m

@@ -0,0 +1,24 @@
+function [ s_hat ] = OMP(x,A,q)
+[N,K] = size(A);
+s_hat= zeros(K,1);
+r=x;
+T=[];
+for i=1:K
+norms(i)=norm(A(:,i));
+end
+for ii = 1:q
+    g= A'*r;
+    for b3=1:K
+        f(b3)=abs(g(b3))/norms(b3);
+    end
+    jj = find(f == max(f));
+    T = union(T,jj);
+    s_hat(T)=pinv(A(:,T)) * x;  %%coeffecient update
+    r=x-A*s_hat;   %%residu update
+    if (mse(x,s_hat) < .1)
+        break;
+    end
+end
+
+
+