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Semiconvergence of parallel multisplitting methods for symmetric positive semidefinite linear systems
Author(s) -
Cao Guangxi,
Song Yongzhong
Publication year - 2011
Publication title -
numerical linear algebra with applications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.02
H-Index - 53
eISSN - 1099-1506
pISSN - 1070-5325
DOI - 10.1002/nla.721
Subject(s) - invertible matrix , mathematics , positive definite matrix , linear system , diagonally dominant matrix , construct (python library) , singular value , pure mathematics , mathematical analysis , computer science , eigenvalues and eigenvectors , physics , quantum mechanics , programming language
In this paper we construct some parallel relaxed multisplitting methods for solving consistent symmetric positive semidefinite linear systems, based on modified diagonally compensated reduction and incomplete factorizations. The semiconvergence of the parallel multisplitting method, relaxed multisplitting method and relaxed two‐stage multisplitting method are discussed. The results generalize some well‐known results for the nonsingular linear systems to the singular systems. Copyright © 2010 John Wiley & Sons, Ltd.