中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
A globally convergent Newton-GMRES method for large sparse systems of nonlinear equations

文献类型:期刊论文

作者An, Heng-Bin; Bai, Zhong-Zhi
刊名APPLIED NUMERICAL MATHEMATICS
出版日期2007-03-01
卷号57期号:3页码:235-252
关键词systems of nonlinear equations inexact Newton method GMRES global convergence
ISSN号0168-9274
DOI10.1016/j.apnum.2006.02.007
英文摘要The inexact Newton with backtracking (INB) method is a powerful tool for solving large sparse systems of nonlinear equations. In particular, if the generalized minimal residual (GMRES) method is used to solve the Newton equations, then the Newton-GMRES with backtracking (NGB) method is obtained. In this paper, we present a new class of globally convergent Newton-GMRES methods. In these methods, the typical backtracking strategy is augmented with a new strategy that is invoked when the inexact Newton direction is not satisfactory. Global convergence properties of the proposed methods are established and numerical results are provided, showing that the new method, called the Newton-GMRES with quasi-conjugate-gradient backtracking (NGQCGB), is very robust and effective. (c) 2006 Published by Elsevier B.V. on behalf of IMACS.
WOS研究方向Mathematics
语种英语
WOS记录号WOS:000244648600001
出版者ELSEVIER SCIENCE BV
源URL[http://ir.amss.ac.cn/handle/2S8OKBNM/4070]  
专题计算数学与科学工程计算研究所
通讯作者Bai, Zhong-Zhi
作者单位Chinese Acad Sci, State Key Lab Sci Engn Comp, Inst Computat Math & Sci Engn Comp, Acad Math & Syst Sci, Beijing 100080, Peoples R China
推荐引用方式
GB/T 7714
An, Heng-Bin,Bai, Zhong-Zhi. A globally convergent Newton-GMRES method for large sparse systems of nonlinear equations[J]. APPLIED NUMERICAL MATHEMATICS,2007,57(3):235-252.
APA An, Heng-Bin,&Bai, Zhong-Zhi.(2007).A globally convergent Newton-GMRES method for large sparse systems of nonlinear equations.APPLIED NUMERICAL MATHEMATICS,57(3),235-252.
MLA An, Heng-Bin,et al."A globally convergent Newton-GMRES method for large sparse systems of nonlinear equations".APPLIED NUMERICAL MATHEMATICS 57.3(2007):235-252.

入库方式: OAI收割

来源:数学与系统科学研究院

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