A new conjugate gradient method with a restart direction and its application in image restoration

被引：1
|
作者：
Li, Yixin [1 ]
Li, Chunguang [1 ]
Yang, Wei [1 ]
Zhang, Wensheng [1 ]
机构：
[1] North Minzu Univ, Sch Math & Informat Sci, Yinchuan 750021, Peoples R China
来源：
AIMS MATHEMATICS | 2023年 / 8卷 / 12期
基金：
中国国家自然科学基金;
关键词：
unconstrained optimization; conjugate gradient method; strong Wolfe line search; global convergence; numerical experiment; image restoration; CONVERGENCE CONDITIONS; ALGORITHM;
D O I：
10.3934/math.20231475
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
We established a new conjugate gradient method with an efficient restart direction for solving large scale unconstrained optimization problems. The modified method was proposed under the Polak-Ribie`re-Polyak conjugate gradient method. Under the strong Wolfe line search, the search direction of the new method was sufficiently descent and its global convergence property could be proved. Compared with other methods having good numerical performances, numerical experiments and image restorations showed that the modified method was more effective.
引用
收藏
页码：28791 / 28807
页数：17
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