Two new preconditioned GAOR methods for weighted linear least squares problems

Shu-Xin Miao, Yu-Hua Luo and Guang-Bin Wang

Applied Mathematics and Computation, 2018, vol. 324, issue C, 93-104

Abstract: In this paper, the preconditioned generalized accelerated overrelaxation (GAOR) methods for solving weighted linear least squares problems are considered. Two new preconditioners are proposed and the convergence rates of the new preconditioned GAOR methods are studied. Comparison results show that the convergence rates of the new preconditioned GAOR methods are better than those of the preconditioned GAOR methods in the previous literatures whenever these methods are convergent. A numerical example is given to confirm our theoretical results.

Keywords: Preconditioner; GAOR method; Preconditioned GAOR method; Weighted linear least squares problem; Comparison (search for similar items in EconPapers)
Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:eee:apmaco:v:324:y:2018:i:c:p:93-104

DOI: 10.1016/j.amc.2017.12.007

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