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A class of parallel decomposition-type relaxation methods for large sparse systems of linear equations

机译:大型线性方程组稀疏系统的一类并行分解型松弛方法

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摘要

A class of parallel decomposition-type accelerated over-relaxation methods, including four arbitrary parameters and suitable to the SIMD-systems, is established for solving the large sparse systems of linear equations in this paper, and sufficient conditions ensuring its convergence are deduced when the coefficient matrices of the linear systems of equations are respectively L-matrices, H-matrices and positive definite matrices. In particular, we investigate in detail the symmetric versions of these new methods, and deduce a series of conveniently applicable conditions for determining the convergence of these versions when the coefficient matrices of the linear systems of equations are symmetric positive definite matrices. (C) 1998 Elsevier Science Inc. All rights reserved. [References: 18]
机译:针对一类大型稀疏线性方程组,建立了一类包括四个任意参数且适用于SIMD系统的并行分解式加速过松弛方法,并通过充分条件推导了其收敛性。线性方程组的系数矩阵分别为L矩阵,H矩阵和正定矩阵。特别是,我们详细研究了这些新方法的对称形式,并推导出了当方程线性系统的系数矩阵为对称正定矩阵时确定这些形式的收敛性的一系列方便适用的条件。 (C)1998 Elsevier Science Inc.保留所有权利。 [参考:18]

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