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Regularized DPSS preconditioners for generalized saddle point linear systems
- Source :
- Computers & Mathematics with Applications. 80:956-972
- Publication Year :
- 2020
- Publisher :
- Elsevier BV, 2020.
-
Abstract
- By introducing a regularization matrix and an additional iteration parameter, a new class of regularized deteriorated positive-definite and skew-Hermitian splitting (RDPSS) preconditioners are proposed for generalized saddle point linear systems. Compared with the well-known Hermitian and skew-Hermitian splitting (HSS) preconditioner and the regularized HSS preconditioner (Bai, 2019) studied recently, the new RDPSS preconditioners have much better computing efficiency especially when the (1,1) block matrix is non-Hermitian. It is proved that the corresponding RDPSS stationary iteration method is unconditionally convergent. In addition, clustering property of the eigenvalues of the RDPSS preconditioned matrix is studied in detail. Two numerical experiments arising from the meshfree discretization of a static piezoelectric equation and the finite element discretization of the Navier–Stokes equation show the effectiveness of the new proposed preconditioners.
- Subjects :
- Discretization
Iterative method
Preconditioner
Linear system
Block matrix
010103 numerical & computational mathematics
Computer Science::Numerical Analysis
01 natural sciences
Hermitian matrix
Mathematics::Numerical Analysis
010101 applied mathematics
Computational Mathematics
Computational Theory and Mathematics
Modeling and Simulation
Saddle point
Applied mathematics
0101 mathematics
Eigenvalues and eigenvectors
Mathematics
Subjects
Details
- ISSN :
- 08981221
- Volume :
- 80
- Database :
- OpenAIRE
- Journal :
- Computers & Mathematics with Applications
- Accession number :
- edsair.doi...........e039d0a831f1bc7d708e5183065f07d4