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Minimum residual NDSS iteration method for a class of complex symmetric linear systems.

Authors :
Xiao, Yao
Wu, Qingbiao
Zhang, Yuanyuan
Source :
Journal of Computational & Applied Mathematics. Oct2024, Vol. 449, pN.PAG-N.PAG. 1p.
Publication Year :
2024

Abstract

The double-step scale splitting and the minimum residual modified HSS iteration method are effective methods for a class of large sparse complex symmetric systems of linear equations. In this paper, we give an efficient method to solve the linear equations related to complex symmetric systems. Firstly, we modify the double-step scale splitting (DSS) iteration methods, obtaining the new double-step scale splitting (NDSS) iteration methods. Furthermore, we improve the algorithm by taking use of minimum residual technique. We call the modified algorithm minimum residual NDSS (MRNDSS) iteration method. For the new presented method, we study some properties of the algorithm carefully. Compared with the NDSS method, MRNDSS has two different parameters in each alternating iteration step and two additional parameters depending on the residual error from previous step. In our numerical experiments, our new method performs more efficient than four other iteration methods which are usually applied to solve the same problems. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
03770427
Volume :
449
Database :
Academic Search Index
Journal :
Journal of Computational & Applied Mathematics
Publication Type :
Academic Journal
Accession number :
177653472
Full Text :
https://doi.org/10.1016/j.cam.2024.115923