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
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
收藏
页码:874 / 894
页数:21
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