On the Some New Preconditioned Generalized AOR Methods for Solving Weighted Linear Least Squares Problems

被引：6

作者：

Fallah, M. ^{[1
]}

Edalatpanah, S. A. ^{[2
]}

机构：

[1] Islamic Azad Univ, Dept Ind Engn, Cent Tehran Branch, Tehran 4695113111, Iran

[2] Ayandegan Inst Higher Educ, Dept Appl Math, Tonekabon 4684161167, Iran

来源：

IEEE ACCESS | 2020年 / 8卷

关键词：

Preconditioned GAOR method; weighted linear least squares problems; linear system; convergence; comparison theorem; CONVERGENCE; SYSTEMS;

D O I：

10.1109/ACCESS.2020.2973289

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Recently, in the paper [Z.G. Huang, L.G. Wang, Z. Xu, J.J. Cui, Some new preconditioned generalized AOR methods for solving weighted linear least squares problems, Computational and Applied Mathematics, 37(2018) 415-438.], Huang et al, by using the generalized accelerated over-relaxation (GAOR) methods, proposed some new preconditioners for solving weighted linear least squares problems and discuss their comparison results. In this paper, we present a new model of GAOR methods to solve the weighted linear least squares problems. We prove that the new model is superior to the existing mentioned methods. Numerical examples are also reported to confirm our theoretical analysis.

引用

页码：33196 / 33201

页数：6

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