An improved generalized parameterized inexact Uzawa method for singular saddle point problems

被引:0
|
作者
Zhang, Li-Tao [1 ]
Shi, Li-Min [1 ]
机构
[1] Zhengzhou Univ Aeronaut, Coll Sci, Zhengzhou 450015, Henan, Peoples R China
基金
中国博士后科学基金;
关键词
Krylov subspace methods; Generalized saddle point matrices; Minimal polynomial; Preconditioners; CONJUGATE-GRADIENT METHODS; PRECONDITIONERS;
D O I
暂无
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
In this paper, based on the generalized parameterized inexact Uzawa method (GPIU) presented by Zhang and Wang [Applied Mathematics and Computation, 219(2013) 4225-4231], we introduce and study an improved generalized parameterized inexact Uzawa method (IG-PIU) for singular saddle point problems. Moreover, theoretical analysis shows that the semi-convergence of the IGPIU method can be guaranteed by suitable choices of the iteration parameters. Finally, numerical experiments are carried out, which show that the improved generalized parameterized inexact Uzawa method (IGPIU) with appropriate parameters improve the convergence of iteration method efficiently when solving singular saddle point problems from the classic incompressible steady state Stokes problems.
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页码:671 / 683
页数:13
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