Efficient preconditioned NHSS iteration methods for solving complex symmetric linear systems

Based on the new HSS (NHSS) iteration method introduced by Pour and Goughery (2015), we propose a preconditioned variant of NHSS (P*NHSS) and an efficient parameterized P*NHSS (PPNHSS) iteration methods for solving a class of complex symmetric linear systems. The convergence properties of the P*NHSS...

Full description

Saved in:
Bibliographic Details
Published inComputers & mathematics with applications (1987) Vol. 75; no. 1; pp. 235 - 247
Main Authors Xiao, Xiao-Yong, Wang, Xiang, Yin, Hong-Wei
Format Journal Article
LanguageEnglish
Published Oxford Elsevier Ltd 01.01.2018
Elsevier BV
Subjects
Complex symmetric linear system
Convergence
Convergence analysis
HSS iteration
Iterative methods
Linear systems
Parameters
Positive definite
Sequences
Spectral radius
Symmetry
Upper bounds
Positive definite
Complex symmetric linear system
Spectral radius
HSS iteration
Convergence analysis
Online AccessGet full text

Cover

More Information
Summary:Based on the new HSS (NHSS) iteration method introduced by Pour and Goughery (2015), we propose a preconditioned variant of NHSS (P*NHSS) and an efficient parameterized P*NHSS (PPNHSS) iteration methods for solving a class of complex symmetric linear systems. The convergence properties of the P*NHSS and the PPNHSS iteration methods show that the iterative sequences are convergent to the unique solution of the linear system for any initial guess when the parameters are properly chosen. Moreover, we discuss the quasi-optimal parameters which minimize the upper bounds for the spectral radius of the iteration matrices. Numerical results show that the PPNHSS iteration method is superior to several iteration methods whether the experimental optimal parameters are used or not.
ISSN:0898-1221
1873-7668
DOI:10.1016/j.camwa.2017.09.004