Convex Variational Formulation with Smooth Coupling for Multicomponent Signal Decomposition and Recovery

作     者：Luis M.Briceo-Arias Patrick L.Combettes 

作者机构：UPMC Universite Paris 06Laboratoire Jacques-Louis Lions-UMR 7598 and Equipe Combinatoire et Optimisation-UMR 7090 UPMC Universite Paris 06Laboratoire Jacques-Louis Lions-UMR 7598 

出 版 物：《Numerical Mathematics(Theory,Methods and Applications)》 (高等学校计算数学学报（英文版）)

年 卷 期：2009年第2卷第4期

页      面：485-508页

核心收录：

学科分类：07[理学] 070104[理学-应用数学] 0701[理学-数学] 

基　　金：supported by the Agence Nationale de la Recherche under grant ANR-08-BLAN-0294-02 

主　　题：Convex optimization denoising image restoration proximal algorithm signal decom-position signal recovery 

摘      要：A convex variational formulation is proposed to solve multicomponent signal processing problems in Hilbert *** cost function consists of a separable term, in which each component is modeled through its own potential,and of a coupling term, in which constraints on linear transformations of the components are penalized with smooth *** algorithm with guaranteed weak convergence to a solution to the problem is *** multicomponent signal decomposition and recovery applications are discussed.