A parallel multisplitting method with self-adaptive weightings for solving H-matrix linear systemsReport as inadecuate




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Journal of Inequalities and Applications

, 2017:95

First Online: 01 May 2017Received: 17 January 2017Accepted: 19 April 2017DOI: 10.1186-s13660-017-1370-7

Cite this article as: Wen, R. & Duan, H. J Inequal Appl 2017 2017: 95. doi:10.1186-s13660-017-1370-7

Abstract

In this paper, a parallel multisplitting iterative method with the self-adaptive weighting matrices is presented for the linear system of equations when the coefficient matrix is an H-matrix. The zero pattern in weighting matrices is determined in advance, while the non-zero entries of weighting matrices are determined by finding the optimal solution in a hyperplane of α points generated by the parallel multisplitting iterations. Especially, the nonnegative restriction of weighting matrices is released. The convergence theory is established for the parallel multisplitting method with self-adaptive weightings. Finally, a numerical example shows that the parallel multisplitting iterative method with the self-adaptive weighting matrices is effective.

Keywordslinear systems self-adaptive weightings convergence parallel multisplitting H-matrix 



Author: Ruiping Wen - Hui Duan

Source: https://link.springer.com/



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