A general class of constraint preconditioners for generalized saddle point linear systems

IF 3.4 2区 数学 Q1 MATHEMATICS, APPLIED Applied Mathematics and Computation Pub Date : 2025-03-15 Epub Date: 2024-10-28 DOI:10.1016/j.amc.2024.129148
Hong-Yu Wu
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Abstract

We propose a general class of constraint preconditioners for solving generalized saddle point linear systems, derived from a general matrix splitting of the (1,1) block of the coefficient matrix. This new constraint preconditioner can not only reduce to some existing constraint preconditioners, but also induce new constraint preconditioners under some certain matrix splitting schemes. Then we present invertibility conditions of the proposed constraint preconditioner and establish the convergence analysis of the corresponding constraint preconditioning iteration method. Numerical examples are provided to confirm that the proposed preconditioner outperforms existing ones when suitable matrix splitting schemes are chosen.
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广义鞍点线性系统的一类通用约束预处理器
我们提出了一类用于求解广义鞍点线性系统的通用约束前提器,该约束前提器源于系数矩阵 (1,1) 块的通用矩阵拆分。这种新的约束条件器不仅能还原现有的一些约束条件器,还能在某些矩阵拆分方案下诱导出新的约束条件器。然后,我们提出了所提约束条件的可逆性条件,并建立了相应约束条件迭代方法的收敛性分析。我们提供的数值示例证实,在选择合适的矩阵拆分方案时,所提出的预条件器优于现有的预条件器。
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来源期刊
CiteScore
7.90
自引率
10.00%
发文量
755
审稿时长
36 days
期刊介绍: Applied Mathematics and Computation addresses work at the interface between applied mathematics, numerical computation, and applications of systems – oriented ideas to the physical, biological, social, and behavioral sciences, and emphasizes papers of a computational nature focusing on new algorithms, their analysis and numerical results. In addition to presenting research papers, Applied Mathematics and Computation publishes review articles and single–topics issues.
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