Two self-adaptive inertial projection algorithms for solving split variational inclusion problems

被引:1
|
作者
Zhou, Zheng [1 ]
Tan, Bing [1 ]
Li, Songxiao [1 ]
机构
[1] Univ Elect Sci & Technol China, Inst Fundamental & Frontier Sci, Chengdu 611731, Peoples R China
来源
AIMS MATHEMATICS | 2022年 / 7卷 / 04期
关键词
self-adaptive stepsize; projection algorithm; inertial technique; split variational inclusion problem; STRONG-CONVERGENCE THEOREMS; NONEXPANSIVE-MAPPINGS; ITERATIVE METHOD; POINT; OPERATORS; SEQUENCE;
D O I
10.3934/math.2022276
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
This paper is to analyze the approximation solution of a split variational inclusion problem in the framework of Hilbert spaces. For this purpose, inertial hybrid and shrinking projection algorithms are proposed under the effect of a self-adaptive stepsize which does not require information of the norms of the given operators. The strong convergence properties of the proposed algorithms are obtained under mild constraints. Finally, a numerical experiment is given to illustrate the performance of proposed methods and to compare our algorithms with an existing algorithm.
引用
收藏
页码:4960 / 4973
页数:14
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