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Block AOR iteration for nonsymmetric matrices


Author: Theodore S. Papatheodorou
Journal: Math. Comp. 41 (1983), 511-525
MSC: Primary 65F50; Secondary 65F10
DOI: https://doi.org/10.1090/S0025-5718-1983-0717699-0
MathSciNet review: 717699
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Abstract: We consider a class of matrices that are of interest to numerical applications and are large, sparse, but not symmetric or diagonally dominant. We give a criterion for the existence of (and we actually construct) the inverse matrix in terms of powers of a "small" matrix. We use this criterion to find that the spectral radius of the Jacobi iteration matrix, corresponding to a block tridiagonal partition, is in general $ \geqslant 1$. We also derive conditions (that are satisfied in cases of interest to applications) for the Jacobi matrix to have spectral radius = 1. We introduce convergent "block AOR" iterative schemes such as extrapolated Jacobi and extrapolated Gauss-Seidel schemes with optimum (under) relaxation parameter $ \omega = .5$. A numerical example pertaining to the solution of Poisson's equation is given, as a demonstration of some of our hypotheses and results. A comparison with SOR, applied to the 5-point finite difference method, is also included.


References [Enhancements On Off] (What's this?)

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Additional Information

DOI: https://doi.org/10.1090/S0025-5718-1983-0717699-0
Keywords: AOR iteration
Article copyright: © Copyright 1983 American Mathematical Society

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