A block product preconditioner for saddle point problems

被引：5

作者：

Liao, Li-Dan ^{[1
,2
]}

Zhang, Guo-Feng ^{[1
]}

Zhu, Mu-Zheng ^{[3
]}

机构：

[1] Lanzhou Univ, Sch Math & Stat, Lanzhou 730000, Gansu, Peoples R China

[2] Nanchang Univ, Dept Math, Nanchang 330031, Jiangxi, Peoples R China

[3] Hexi Univ, Sch Math & Stat, Zhangye 734000, Peoples R China

来源：

JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS | 2019年 / 352卷

基金：

中国国家自然科学基金;

关键词：

Saddle point problems; Preconditioner; Spectral properties; Optimal parameter; Krylov subspace method; CONJUGATE-GRADIENT METHODS; SPLITTING ITERATION METHODS; TRIANGULAR PRECONDITIONERS; UZAWA METHODS; OPTIMAL PARAMETERS;

D O I：

10.1016/j.cam.2018.11.026

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

In this paper, a block product (BP) preconditioner is established for saddle point problems. Spectral properties of the BP preconditioned matrix are investigated. A strategy for practical choice of quasi-optimal parameter is given. Numerical results on saddle point linear systems arising from Stokes problems and weighted least square problems show that the proposed BP preconditioner is more economic to implement within Krylov subspace acceleration than some extensively studied preconditioners. (C) 2018 Elsevier B.V. All rights reserved.

引用

页码：426 / 436

页数：11

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