@Article{EAJAM-14-4,
author = {Zhang, Hui and Hua, Dai},
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 = {<p style="text-align: justify;">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.</p>},
issn = {2079-7370},
doi = {https://doi.org/10.4208/eajam.2023-161.081023},
url = {https://global-sci.com/article/91351/the-regularized-global-gmerr-method-for-solving-large-scale-linear-discrete-ill-posed-problems}
}