吉林大学学报（理学版）2026，Vol.64Issue(3)：521-527,7.DOI:10.13413/j.cnki.jdxblxb.2025229
求解单调变分包含问题的自适应-正则化方法及应用
Adaptive Regularization Method for Solving Monotonic Variational Inclusion Problems and Applications
摘要
Abstract
We gave an adaptive regularization method for solving monotonic variational inclusion problems in Hilbert space.Firstly,we used adaptive rules to eliminate the dependence of iterative step-sizes on operators in the convergence analysis of existing algorithms.Secondly,we combined regularization technique to establish strong convergence theorems for solving variational inclusion problems.Finally,the convergence and superiority of the proposed algorithm were demonstrated through image reconstruction experiment.关键词
变分包含问题/自适应算法/正则化/强收敛/图像重建Key words
variational inclusion problem/adaptive algorithm/regularization/strong convergence/image reconstruction分类
数理科学引用本文复制引用
胡洪溧,李倩,张弘飏,闻道君..求解单调变分包含问题的自适应-正则化方法及应用[J].吉林大学学报（理学版）,2026,64(3):521-527,7.基金项目
国家自然科学基金(批准号:11471059)、重庆市自然科学基金(批准号:cstc2020jcyj-msxmX0316)和重庆工商大学研究生科研创新项目(批准号:yjsc-xx2025-269-245). （批准号:11471059）
