Variable metric quasi-Fejer monotonicity

作     者：Combettes, Patrick L. Vu, Bang C. 

作者机构：Univ Paris 06 CNRS Lab Jacques Louis Lions UMR 7598 F-75005 Paris France 

出 版 物：《NONLINEAR ANALYSIS-THEORY METHODS & APPLICATIONS》 (非线性分析)

年 卷 期：2013年第78卷第1期

页      面：17-31页

核心收录：

学科分类：07[理学] 0701[理学-数学] 070101[理学-基础数学] 

基　　金：Vietnam National Foundation for Science and Technology Development (NAFOSTED) [102.01-2012.15] 

主　　题：Convex feasibility problem Convex optimization Hilbert space Inverse problems Proximal Landweber method Proximal point algorithm Quasi-Fejer sequence Variable metric 

摘      要：The notion of quasi-Fejer monotonicity has proven to be an efficient tool to simplify and unify the convergence analysis of various algorithms arising in applied nonlinear analysis. In this paper, we extend this notion in the context of variable metric algorithms, whereby the underlying norm is allowed to vary at each iteration. Applications to convex optimization and inverse problems are demonstrated. (c) 2012 Elsevier Ltd. All rights reserved.