基于正弦变换的空间分数扩散方程预处理技术

IF 1.8 3区 数学 Q1 MATHEMATICS
H. Qin, Hong-Kui Pang, Hai-wei Sun
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引用次数: 2

摘要

我们研究了由多维空间分数阶扩散方程数值解产生的线性系统的预条件迭代方法。根据Toeplitz因子在所得系数矩阵中的对称和斜对称分解,开发了一种基于正弦变换的预处理技术。理论分析表明,将GMRES方法应用于预处理线性系统时,其相对残差范数的上界与网格无关,这意味着线性收敛性。通过数值实验验证了理论结果的正确性和所提出的预处理技术的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Sine transform based preconditioning techniques for space fractional diffusion equations
We study the preconditioned iterative methods for the linear systems arising from the numerical solution of the multi‐dimensional space fractional diffusion equations. A sine transform based preconditioning technique is developed according to the symmetric and skew‐symmetric splitting of the Toeplitz factor in the resulting coefficient matrix. Theoretical analyses show that the upper bound of relative residual norm of the GMRES method when applied to the preconditioned linear system is mesh‐independent which implies the linear convergence. Numerical experiments are carried out to illustrate the correctness of the theoretical results and the effectiveness of the proposed preconditioning technique.
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来源期刊
CiteScore
3.40
自引率
2.30%
发文量
50
审稿时长
12 months
期刊介绍: Manuscripts submitted to Numerical Linear Algebra with Applications should include large-scale broad-interest applications in which challenging computational results are integral to the approach investigated and analysed. Manuscripts that, in the Editor’s view, do not satisfy these conditions will not be accepted for review. Numerical Linear Algebra with Applications receives submissions in areas that address developing, analysing and applying linear algebra algorithms for solving problems arising in multilinear (tensor) algebra, in statistics, such as Markov Chains, as well as in deterministic and stochastic modelling of large-scale networks, algorithm development, performance analysis or related computational aspects. Topics covered include: Standard and Generalized Conjugate Gradients, Multigrid and Other Iterative Methods; Preconditioning Methods; Direct Solution Methods; Numerical Methods for Eigenproblems; Newton-like Methods for Nonlinear Equations; Parallel and Vectorizable Algorithms in Numerical Linear Algebra; Application of Methods of Numerical Linear Algebra in Science, Engineering and Economics.
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