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A CLASS OF ASYNCHRONOUS PARALLEL NONLINEAR MULTISPLITTING RELAXATION METHODS

 

作者: DEREN WANG,   ZHONGZHI BAI,   D. J. EVANS,  

 

期刊: Parallel Algorithms and Applications  (Taylor Available online 1994)
卷期: Volume 2, issue 3  

页码: 209-228

 

ISSN:1063-7192

 

年代: 1994

 

DOI:10.1080/10637199408915417

 

出版商: Taylor & Francis Group

 

关键词: System of nonlinear equations;nonlinear multisplitting;relaxation;asynchronous iteration;local convergence;G.1.3

 

数据来源: Taylor

 

摘要:

In this paper, we establish a class of asynchronous parallel nonlinear multisplitting relaxation methods for solving system of nonlinear equations. With special choices of the relaxed parameters in the new methods, not only can the convergence properties of them be improved, but also many applicable and efficient asynchronous parallel nonlinear multisplitting iteration methods such as the Jacobi, Gauss-Seidel, SOR as well as the asynchronous parallel nonlinear multisplitting AOR-Newton, -Chord and -Steffensen programs, etc., can be obtained. Under proper conditions, we build convergence theories about these asynchronous methods, and estimate their asymptotic convergence rates in detailed manner.

 

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