New self-adaptive step size algorithms for solving split variational inclusion problems and its applications

被引：36

作者：

Tang, Yan ^{[1
,2
]}

Gibali, Aviv ^{[3
,4
]}

机构：

[1] Chongqing Technol & Business Univ, Coll Math & Stat, Chongqing 400067, Peoples R China

[2] Chongqing Key Lab Social Econ & Appl Stat, Chongqing 400067, Peoples R China

[3] ORT Braude Coll, Dept Math, IL-2161002 Karmiel, Israel

[4] Univ Haifa, Ctr Math & Sci Computat, IL-3498838 Haifa, Israel

来源：

NUMERICAL ALGORITHMS | 2020年 / 83卷 / 01期

基金：

中国国家自然科学基金;

关键词：

Split variational inclusion problem; Convex minimization problems; Self-adaptive; Strong convergence; ITERATIVE ALGORITHMS; STRONG-CONVERGENCE; POINT PROBLEM; FIXED-POINTS; FEASIBILITY; PROJECTION;

D O I：

10.1007/s11075-019-00683-0

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

In this paper, we study a special instance of the split inverse problem (SIP), which is the split variational inclusion problem (SVIP). Three simple iterative methods for solving it are introduced and weak and strong convergence theorems are established under mild and standard assumptions. As an application, the problem of minimizing two proper, convex, and lower semi-continuous functions is considered. We compare and illustrate the efficiency and applicability of our schemes for several numerical experiments as well as an example in the field of compressed sensing.

引用

页码：305 / 331

页数：27

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