The Regularized Global GMERR Method for Solving Large-Scale Linear Discrete Ill-Posed Problems

被引：0

作者：

Zhang, Hui ^{[1
]}

Dai, Hua ^{[1
]}

机构：

[1] Nanjing Univ Aeronaut & Astronaut, Sch Math, Nanjing 210016, Peoples R China

来源：

EAST ASIAN JOURNAL ON APPLIED MATHEMATICS | 2024年 / 14卷 / 04期

基金：

中国国家自然科学基金;

关键词：

Linear discrete ill-posed problems; multiple right-hand sides; global GMERR method; regularizing properties; TIKHONOV REGULARIZATION; LEAST-SQUARES; ITERATIVE REGULARIZATION; ALGORITHM; GMRES; SYSTEMS; SUBSPACE; LSQR; LSMR;

D O I：

10.4208/eajam.2023-161.081023

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

For the large-scale linear discrete ill -posed problems with multiple right-hand sides, the global Krylov subspace iterative methods have received a lot of attention. In this paper, we analyze the regularizing properties of the global generalized minimum error method (GMERR), and develop a regularized global GMERR method for solving linear discrete ill -posed problems with multiple right-hand sides. The efficiency of the proposed method is confirmed by the numerical experiments on test matrices.

引用

页码：874 / 894

页数：21