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A modified parameterized shift-splitting preconditioner for saddle point problems

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Abstract

Inspired by the idea of the parameterized shift-splitting (PSS), this paper presents a modified PSS (MPSS) preconditioner for the generalized nonsymmetric saddle point-type linear systems. All eigenvalues of the corresponding preconditioned matrix are proved to be clustered around 1. Meanwhile, the unconditional convergence of the MPSS iteration method is shown under certain conditions. The proposed method overcomes the shortfalls of the PSS iteration method in Zhang et al. (Math Biosci Eng 16:1021–1033, 2019) for a special case of the considered system. Numerical experiments are provided to validate the theoretical results and illustrate the effectiveness of the proposed preconditioner.

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Acknowledgements

The authors are very much indebted to Prof. Davod Khojasteh Salkuyeh for providing the codes of numerical experiments. We are also thankful to the reviewers for their constructive comments and valuable suggestions, which greatly improved the original manuscript of this paper.

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Correspondence to Xing-Bao Gao.

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Communicated by Joerg Fliege.

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This work is supported by the National Natural Science Foundation of China under Grants 61273311 and 61803247.

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Wu, B., Gao, XB. A modified parameterized shift-splitting preconditioner for saddle point problems. Comp. Appl. Math. 40, 1 (2021). https://doi.org/10.1007/s40314-020-01383-5

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