Convergence of Relaxed Matrix Parallel Multisplitting Chaotic Methods forH -Matrices
Author(s) -
Litao Zhang,
Jianlei Li,
Tong-Xiang Gu,
Xingping Liu
Publication year - 2014
Publication title -
journal of applied mathematics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.307
H-Index - 43
eISSN - 1687-0042
pISSN - 1110-757X
DOI - 10.1155/2014/594185
Subject(s) - convergence (economics) , algorithm , computer science , matrix (chemical analysis) , chaotic , mathematics , diagonal , artificial intelligence , geometry , materials science , composite material , economic growth , economics
Based on the methods presented by Song and Yuan (1994), we construct relaxed matrix parallel multisplitting chaotic generalized USAOR-style methods by introducing more relaxed parameters and analyze the convergence of our methods when coefficient matrices are H-matrices or irreducible diagonally dominant matrices. The parameters can be adjusted suitably so that the convergence property of methods can be substantially improved. Furthermore, we further study some applied convergence results of methods to be convenient for carrying out numerical experiments. Finally, we give some numerical examples, which show that our convergence results are applied and easily carried out
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