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

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

Year:    2024

Author:    Hui Zhang, Hua Dai

East Asian Journal on Applied Mathematics, Vol. 14 (2024), Iss. 4 : pp. 874–894

Abstract

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.

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Journal Article Details

Publisher Name:    Global Science Press

Language:    English

DOI:    https://doi.org/10.4208/eajam.2023-161.081023

East Asian Journal on Applied Mathematics, Vol. 14 (2024), Iss. 4 : pp. 874–894

Published online:    2024-01

AMS Subject Headings:   

Copyright:    COPYRIGHT: © Global Science Press

Pages:    21

Keywords:    Linear discrete ill-posed problems multiple right-hand sides global GMERR method regularizing properties.

Author Details

Hui Zhang

Hua Dai