NANAJun 20, 2018

On Generalized Jacobi, Gauss-Seidel and SOR Methods

arXiv:1806.076821 citationsh-index: 10
Originality Synthesis-oriented
AI Analysis

Incremental extension of iterative methods for solving linear systems, providing new convergence results and a generalized SOR variant.

The paper studies generalized Jacobi and Gauss-Seidel methods, proposes a generalized SOR method, and demonstrates its advantages through numerical experiments with convergence criteria for various matrix classes.

In this paper generalization of Jacobi and Gauss-Seidel methods, introduced by Salkuyeh in 2007, is studied. In particular, convergence criteria for these methods are discussed. A generalization of successive overrelaxation~(SOR) method is proposed, and its convergence properties for various classes of matrices are discussed. Advantages of generalized SOR method are established through numerical experiments.

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