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<p>In this paper, we introduce two iterative parameters to accelerate the regularized deteriorated positive and skew-Hermitian splitting (RDPSS) method for saddle point systems, and propose an accelerated RDPSS (denoted by ARDPSS) iteration method. Theoretically prove the ARDPSS iteration method is unconditional convergence and analyze the eigenvalue clustering properties of the ARDPSS preconditioned matrix. In addition, we conducted a detailed analysis of the optimal likelihood parameters for the ARDPSS method. Finally, numerical experiments verify the theoretical results and demonstrate the feasibility of the ARDPSS preconditioner.</p>

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Accelerated RDPSS iteration methods for saddle point linear systems

  • 期刊论文

  • 发表日期：

    2025年6月10日

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  • XueYun Wen,
  • Zhuo-Hong Huang

摘要

In this paper, we introduce two iterative parameters to accelerate the regularized deteriorated positive and skew-Hermitian splitting (RDPSS) method for saddle point systems, and propose an accelerated RDPSS (denoted by ARDPSS) iteration method. Theoretically prove the ARDPSS iteration method is unconditional convergence and analyze the eigenvalue clustering properties of the ARDPSS preconditioned matrix. In addition, we conducted a detailed analysis of the optimal likelihood parameters for the ARDPSS method. Finally, numerical experiments verify the theoretical results and demonstrate the feasibility of the ARDPSS preconditioner.