On the NESS iteration method for singular saddle point problems

IF 2.6 2区数学 Q1 MATHEMATICS, APPLIED

Journal of Computational and Applied Mathematics Pub Date : 2025-09-23 DOI:10.1016/j.cam.2025.117082

Hong Wang, Nai-Min Zhang

引用次数: 0

Abstract

Recently, Wang and Li (2019) studied a new extended shift-splitting (NESS) iteration method for solving nonsingular saddle point problems. In this paper we investigate the singular NESS (SNESS) preconditioner for solving singular saddle point problems and discuss three SNESS iterations. With the SNESS preconditioner, the splitting of the corresponding coefficient matrix is a proper splitting, which help the three SNESS iterations to converge to the generalized inverse solution. Numerical results demonstrate the effectiveness of the SNESS iterations for solving singular saddle point problems.

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奇异鞍点问题的NESS迭代方法

最近，Wang and Li（2019）研究了一种求解非奇异鞍点问题的扩展位移分裂（NESS）迭代方法。本文研究了求解奇异鞍点问题的奇异NESS （SNESS）预条件，并讨论了三次SNESS迭代。在SNESS预条件下，相应系数矩阵的分裂是一个适当的分裂，这有助于三次SNESS迭代收敛到广义逆解。数值结果证明了该方法对求解奇异鞍点问题的有效性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Journal of Computational and Applied Mathematics 数学-应用数学

CiteScore

5.40

自引率

4.20%

发文量

437

审稿时长

3.0 months

期刊介绍： The Journal of Computational and Applied Mathematics publishes original papers of high scientific value in all areas of computational and applied mathematics. The main interest of the Journal is in papers that describe and analyze new computational techniques for solving scientific or engineering problems. Also the improved analysis, including the effectiveness and applicability, of existing methods and algorithms is of importance. The computational efficiency (e.g. the convergence, stability, accuracy, ...) should be proved and illustrated by nontrivial numerical examples. Papers describing only variants of existing methods, without adding significant new computational properties are not of interest. The audience consists of: applied mathematicians, numerical analysts, computational scientists and engineers.