New proximal type algorithms for convex minimization and its application to image deblurring

被引：0
作者：
Suparat Kesornprom
Prasit Cholamjiak
Choonkil Park
机构：
[1] University of Phayao,School of Science
[2] Research Institute for Natural Sciences,undefined
[3] Hanyang University,undefined
来源：
Computational and Applied Mathematics | 2022年 / 41卷
关键词：
Convex minimization problem; Forward–backward method; Linesearch rule; Inertial method; Weak convergence; 65K05; 90C25; 90C30;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
In this work, we are interested in solving a convex minimization problem in real Hilbert spaces. We propose a new modified proximal algorithm using the inertial extrapolation and the linesearch technique. Its weak convergence theorems are established under mild conditions. Numerical experiments are presented to illustrate the performance of the proposed algorithm in image deblurring.
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