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SOR-like Methods with Optimization Model for Augmented Linear Systems

Published online by Cambridge University Press:  31 January 2017

Rui-Ping Wen
Affiliation:
Department of Mathematics, Taiyuan Normal University, Taiyuan, 030012, China
Su-Dan Li
Affiliation:
Department of Mathematics, Taiyuan Normal University, Taiyuan, 030012, China
Guo-Yan Meng
Affiliation:
Department of Mathematics, Xinzhou Teachers College, Xinzhou, 034000, China
Corresponding
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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.

Type
Research Article
Copyright
Copyright © Global-Science Press 2017 

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References

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