Proximal and Lagrangian Penalization Algorithms : Applications to Optimization PDE’S and Compressive Sensing

Abstract

We study some algorithms using proximal, Lagrangian and penalization meth- ods. We prove that the sequences generated by these algorithms converge toward solutions ofminimization problems. Applications are given in the areas of domain decomposition for PDE’s and compressive sensing.