Year: 2017
East Asian Journal on Applied Mathematics, Vol. 7 (2017), Iss. 1 : pp. 101–115
Abstract
There has been a lot of study on the SOR-like methods for solving the augmented system of linear equations since the outstanding work of Golub, Wu and Yuan (BIT 41(2001)71-85) was presented fifteen years ago. Based on the SOR-like methods, we establish a class of accelerated SOR-like methods for large sparse augmented linear systems by making use of optimization technique, which will find the optimal relaxation parameter ω by optimization models. We demonstrate the convergence theory of the new methods under suitable restrictions. The numerical examples show these methods are effective.
You do not have full access to this article.
Already a Subscriber? Sign in as an individual or via your institution
Journal Article Details
Publisher Name: Global Science Press
Language: English
DOI: https://doi.org/10.4208/eajam.010916.261116a
East Asian Journal on Applied Mathematics, Vol. 7 (2017), Iss. 1 : pp. 101–115
Published online: 2017-01
AMS Subject Headings:
Copyright: COPYRIGHT: © Global Science Press
Pages: 15
Keywords: SOR-like method optimization augmented linear systems convergence.
-
Some generalizations of the new SOR-like method for solving symmetric saddle-point problems
Wen, Ruiping | Wu, Ruihuan | Guan, JinruiJournal of Inequalities and Applications, Vol. 2018 (2018), Iss. 1
https://doi.org/10.1186/s13660-018-1738-3 [Citations: 1] -
A semi-smoothing augmented Lagrange multiplier algorithm for low-rank Toeplitz matrix completion
Wen, Ruiping | Li, Shuzhen | Duan, YonghongJournal of Inequalities and Applications, Vol. 2019 (2019), Iss. 1
https://doi.org/10.1186/s13660-019-2033-7 [Citations: 1]