Numerische Mathematik

, Volume 102, Issue 1, pp 1–38

On generalized successive overrelaxation methods for augmented linear systems

Authors

    • State Key Laboratory of Scientific/Engineering Computing, Institute of Computational Mathematics and Scientific/Engineering ComputingAcademy of Mathematics and System Sciences, Chinese Academy of Sciences
  • Beresford N. Parlett
    • Mathematics Department and Computer Science Division, EECS DepartmentUniversity of California
  • Zeng-Qi Wang
    • State Key Laboratory of Scientific/Engineering Computing, Institute of Computational Mathematics and Scientific/Engineering ComputingAcademy of Mathematics and System Sciences, Chinese Academy of Sciences
Article

DOI: 10.1007/s00211-005-0643-0

Cite this article as:
Bai, Z., Parlett, B. & Wang, Z. Numer. Math. (2005) 102: 1. doi:10.1007/s00211-005-0643-0

Abstract

For the augmented system of linear equations, Golub, Wu and Yuan recently studied an SOR-like method (BIT 41(2001)71–85). By further accelerating it with another parameter, in this paper we present a generalized SOR (GSOR) method for the augmented linear system. We prove its convergence under suitable restrictions on the iteration parameters, and determine its optimal iteration parameters and the corresponding optimal convergence factor. Theoretical analyses show that the GSOR method has faster asymptotic convergence rate than the SOR-like method. Also numerical results show that the GSOR method is more effective than the SOR-like method when they are applied to solve the augmented linear system. This GSOR method is further generalized to obtain a framework of the relaxed splitting iterative methods for solving both symmetric and nonsymmetric augmented linear systems by using the techniques of vector extrapolation, matrix relaxation and inexact iteration. Besides, we also demonstrate a complete version about the convergence theory of the SOR-like method.

Mathematics Subject Classification (2000)

65F1065F50CR: G1.3
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© Springer-Verlag Berlin Heidelberg 2005