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Volume 14, Issue 4
The Regularized Global GMERR Method for Solving Large-Scale Linear Discrete Ill-Posed Problems

Hui Zhang & Hua Dai

East Asian J. Appl. Math., 14 (2024), pp. 874-894.

Published online: 2024-09

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  • 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.

  • AMS Subject Headings

65F10, 65F22

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COPYRIGHT: © Global Science Press

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@Article{EAJAM-14-874, author = {Zhang , Hui and Dai , Hua}, title = {The Regularized Global GMERR Method for Solving Large-Scale Linear Discrete Ill-Posed Problems}, journal = {East Asian Journal on Applied Mathematics}, year = {2024}, volume = {14}, number = {4}, pages = {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.

}, issn = {2079-7370}, doi = {https://doi.org/10.4208/eajam.2023-161.081023}, url = {http://global-sci.org/intro/article_detail/eajam/23441.html} }
TY - JOUR T1 - The Regularized Global GMERR Method for Solving Large-Scale Linear Discrete Ill-Posed Problems AU - Zhang , Hui AU - Dai , Hua JO - East Asian Journal on Applied Mathematics VL - 4 SP - 874 EP - 894 PY - 2024 DA - 2024/09 SN - 14 DO - http://doi.org/10.4208/eajam.2023-161.081023 UR - https://global-sci.org/intro/article_detail/eajam/23441.html KW - Linear discrete ill-posed problems, multiple right-hand sides, global GMERR method, regularizing properties. AB -

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.

Zhang , Hui and Dai , Hua. (2024). The Regularized Global GMERR Method for Solving Large-Scale Linear Discrete Ill-Posed Problems. East Asian Journal on Applied Mathematics. 14 (4). 874-894. doi:10.4208/eajam.2023-161.081023
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