Abstract
For the large sparse generalized saddle point problems with non-Hermitian (1,1) blocks, we introduce a constraint preconditioner, which is based on the positive definite and semidefinite splitting (PPS) iteration method. Then we discuss one trait of the PPS-based constraint preconditioner, such as invertibility. We give the convergence of conditions of the preconditioning iteration method. Moreover, numerical experiments are given to illustrate that PPS-based constraint preconditioner has an obvious advantage of efficiency.
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Acknowledgements
The authors would like to express their great thankfulness to the referees for the comments and constructive suggestions, which were valuable in improving the quality of the original paper. The project was supported by the National Natural Science Foundation of China (No. 11371081) and Liaoning Natural Science Foundation (No. 20170540323).
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Communicated by Jinyun Yuan.
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Shen, HL., Wu, HY., Shao, XH. et al. The PPS method-based constraint preconditioners for generalized saddle point problems. Comp. Appl. Math. 38, 21 (2019). https://doi.org/10.1007/s40314-019-0792-x
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DOI: https://doi.org/10.1007/s40314-019-0792-x
Keywords
- Generalized saddle point problems
- Non-Hermitian matrix
- Positive definite matrix
- Constraint
- Preconditioner