Majorization–minimization for blind source separation of sparse sources

In this paper we propose the Majorization–Minimization Blind Spare Source Separation (MM-BSSS) algorithm for solving the blind source separation (BSS) problem when the source signals are known a priori to be sparse, or can be sparsely represented in some dictionary. The algorithm capitalizes on a previous result by Chartrand (2007 [24]) that shows certain classes of nonconvex functions perform better than the convex ℓ1-norm in measuring …