Recovery of low rank and joint Sparse matrix using Split Bregman

Recovery of low rank and joint sparse matrix using Split Bregman, via nuclear norm & L21minimization

This work deals with recovering a low rank and joint sparse matrix from its lower dimensional projections via nuclear norm and L21 minimization.
% Minimize ||X||*+||DX||2,1 (nuclear norm +l21 norm)
% Subject to A(X) = Y
We use split Bregman algorithm for the same.
% Minimize 1/2||y-Ax||^2 +lambda1||W||* +lambda2||DZ||2,1 +eta1/2||W-X-B1||^2
+eta2/2||Z-X-B2||^2
%W and Z are proxy variables
B1 and B2 are the Bregman variables
The use of Bregman technique improves the convergence and the accuracy of reconstruction.