Volume 7, Issue 1
A Modified Relaxed Positive-Semidefinite and Skew-Hermitian Splitting Preconditioner for Generalized Saddle Point Problems

Yang Cao, An Wang & Yu-Juan Chen

East Asian J. Appl. Math., 7 (2017), pp. 192-210.

Published online: 2018-02

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  • Abstract

Based on the relaxed factorization techniques studied recently and the idea of the simple-like preconditioner, a modified relaxed positive-semidefinite and skewHermitian splitting (MRPSS) preconditioner is proposed for generalized saddle point problems. Some properties, including the eigenvalue distribution, the eigenvector distribution and the minimal polynomial of the preconditioned matrix are studied. Numerical examples arising from the mixed finite element discretization of the Oseen equation are illustrated to show the efficiency of the new preconditioner.

  • Keywords

Generalized saddle point problems, positive-semidefinite and skew-Hermitian splitting, preconditioning, Krylov subspace method.

  • AMS Subject Headings

65F10, 65F50

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COPYRIGHT: © Global Science Press

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@Article{EAJAM-7-192, author = {}, title = {A Modified Relaxed Positive-Semidefinite and Skew-Hermitian Splitting Preconditioner for Generalized Saddle Point Problems}, journal = {East Asian Journal on Applied Mathematics}, year = {2018}, volume = {7}, number = {1}, pages = {192--210}, abstract = {

Based on the relaxed factorization techniques studied recently and the idea of the simple-like preconditioner, a modified relaxed positive-semidefinite and skewHermitian splitting (MRPSS) preconditioner is proposed for generalized saddle point problems. Some properties, including the eigenvalue distribution, the eigenvector distribution and the minimal polynomial of the preconditioned matrix are studied. Numerical examples arising from the mixed finite element discretization of the Oseen equation are illustrated to show the efficiency of the new preconditioner.

}, issn = {2079-7370}, doi = {https://doi.org/10.4208/eajam.190716.311216a}, url = {http://global-sci.org/intro/article_detail/eajam/10743.html} }
TY - JOUR T1 - A Modified Relaxed Positive-Semidefinite and Skew-Hermitian Splitting Preconditioner for Generalized Saddle Point Problems JO - East Asian Journal on Applied Mathematics VL - 1 SP - 192 EP - 210 PY - 2018 DA - 2018/02 SN - 7 DO - http://doi.org/10.4208/eajam.190716.311216a UR - https://global-sci.org/intro/article_detail/eajam/10743.html KW - Generalized saddle point problems, positive-semidefinite and skew-Hermitian splitting, preconditioning, Krylov subspace method. AB -

Based on the relaxed factorization techniques studied recently and the idea of the simple-like preconditioner, a modified relaxed positive-semidefinite and skewHermitian splitting (MRPSS) preconditioner is proposed for generalized saddle point problems. Some properties, including the eigenvalue distribution, the eigenvector distribution and the minimal polynomial of the preconditioned matrix are studied. Numerical examples arising from the mixed finite element discretization of the Oseen equation are illustrated to show the efficiency of the new preconditioner.

Yang Cao, An Wang & Yu-Juan Chen. (2020). A Modified Relaxed Positive-Semidefinite and Skew-Hermitian Splitting Preconditioner for Generalized Saddle Point Problems. East Asian Journal on Applied Mathematics. 7 (1). 192-210. doi:10.4208/eajam.190716.311216a
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