Preconditioned conjugate gradient method and generalized successive overrelaxation method for the least squares problems

被引：3
|
作者：
Li, CJ [1 ]
Evans, DJ
机构：
[1] Chinese Acad Sci, Shenyang Inst Automat, Shenyang, Peoples R China
[2] Northeastern Univ, Shenyang, Peoples R China
[3] Nottingham Trent Univ, Nottingham, England
来源：
INTERNATIONAL JOURNAL OF COMPUTER MATHEMATICS | 2002年 / 79卷 / 05期
基金：
中国国家自然科学基金;
关键词：
least squares problems; generalized successive overrelaxation method; preconditioned conjugate gradient method;
D O I：
10.1080/00207160210949
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
In a recent paper [4], Li et al. gave a generalized successive overrelaxation (GSOR) method for the least squares problems. In this paper, the connection between the GSOR method and the preconditioned conjugate gradient (PCG) method for the normal equations is investigated. It is shown that the PCG method is at least as fast as the GSOR method. Numerical examples demonstrates that the PCG method is much faster than the GSOR method.
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页码：593 / 602
页数：10
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