Residual iterative schemes for large-scale nonsymmetric positive definite linear systems

Detalhes bibliográficos
Autor(a) principal: La Cruz,William
Data de Publicação: 2008
Outros Autores: Raydan,Marcos
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Computational & Applied Mathematics
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1807-03022008000200003
Resumo: A new iterative scheme that uses the residual vector as search direction is proposed and analyzed for solving large-scale nonsymmetric linear systems, whose matrix has a positive (or negative) definite symmetric part. It is closely related to Richardson's method, although the stepsize and some other new features are inspired by the success of recently proposed residual methods for nonlinear systems. Numerical experiments are included to show that, without preconditioning, the proposed scheme outperforms some recently proposed variations on Richardson's method, and competes with well-known and well-established Krylov subspace methods: GMRES and BiCGSTAB. Our computational experiments also show that, in the presence of suitable preconditioning strategies, residual iterative methods can be competitive, and sometimes advantageous, when compared with Krylov subspace methods.
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spelling Residual iterative schemes for large-scale nonsymmetric positive definite linear systemslinear systemsRichardson's methodKrylov subspace methodsspectral gradient methodA new iterative scheme that uses the residual vector as search direction is proposed and analyzed for solving large-scale nonsymmetric linear systems, whose matrix has a positive (or negative) definite symmetric part. It is closely related to Richardson's method, although the stepsize and some other new features are inspired by the success of recently proposed residual methods for nonlinear systems. Numerical experiments are included to show that, without preconditioning, the proposed scheme outperforms some recently proposed variations on Richardson's method, and competes with well-known and well-established Krylov subspace methods: GMRES and BiCGSTAB. Our computational experiments also show that, in the presence of suitable preconditioning strategies, residual iterative methods can be competitive, and sometimes advantageous, when compared with Krylov subspace methods.Sociedade Brasileira de Matemática Aplicada e Computacional2008-01-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S1807-03022008000200003Computational & Applied Mathematics v.27 n.2 2008reponame:Computational & Applied Mathematicsinstname:Sociedade Brasileira de Matemática Aplicada e Computacional (SBMAC)instacron:SBMAC10.1590/S0101-82052008000200003info:eu-repo/semantics/openAccessLa Cruz,WilliamRaydan,Marcoseng2008-07-21T00:00:00Zoai:scielo:S1807-03022008000200003Revistahttps://www.scielo.br/j/cam/ONGhttps://old.scielo.br/oai/scielo-oai.php||sbmac@sbmac.org.br1807-03022238-3603opendoar:2008-07-21T00:00Computational & Applied Mathematics - Sociedade Brasileira de Matemática Aplicada e Computacional (SBMAC)false
dc.title.none.fl_str_mv Residual iterative schemes for large-scale nonsymmetric positive definite linear systems
title Residual iterative schemes for large-scale nonsymmetric positive definite linear systems
spellingShingle Residual iterative schemes for large-scale nonsymmetric positive definite linear systems
La Cruz,William
linear systems
Richardson's method
Krylov subspace methods
spectral gradient method
title_short Residual iterative schemes for large-scale nonsymmetric positive definite linear systems
title_full Residual iterative schemes for large-scale nonsymmetric positive definite linear systems
title_fullStr Residual iterative schemes for large-scale nonsymmetric positive definite linear systems
title_full_unstemmed Residual iterative schemes for large-scale nonsymmetric positive definite linear systems
title_sort Residual iterative schemes for large-scale nonsymmetric positive definite linear systems
author La Cruz,William
author_facet La Cruz,William
Raydan,Marcos
author_role author
author2 Raydan,Marcos
author2_role author
dc.contributor.author.fl_str_mv La Cruz,William
Raydan,Marcos
dc.subject.por.fl_str_mv linear systems
Richardson's method
Krylov subspace methods
spectral gradient method
topic linear systems
Richardson's method
Krylov subspace methods
spectral gradient method
description A new iterative scheme that uses the residual vector as search direction is proposed and analyzed for solving large-scale nonsymmetric linear systems, whose matrix has a positive (or negative) definite symmetric part. It is closely related to Richardson's method, although the stepsize and some other new features are inspired by the success of recently proposed residual methods for nonlinear systems. Numerical experiments are included to show that, without preconditioning, the proposed scheme outperforms some recently proposed variations on Richardson's method, and competes with well-known and well-established Krylov subspace methods: GMRES and BiCGSTAB. Our computational experiments also show that, in the presence of suitable preconditioning strategies, residual iterative methods can be competitive, and sometimes advantageous, when compared with Krylov subspace methods.
publishDate 2008
dc.date.none.fl_str_mv 2008-01-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
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dc.identifier.uri.fl_str_mv http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1807-03022008000200003
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dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/S0101-82052008000200003
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
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dc.format.none.fl_str_mv text/html
dc.publisher.none.fl_str_mv Sociedade Brasileira de Matemática Aplicada e Computacional
publisher.none.fl_str_mv Sociedade Brasileira de Matemática Aplicada e Computacional
dc.source.none.fl_str_mv Computational & Applied Mathematics v.27 n.2 2008
reponame:Computational & Applied Mathematics
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repository.name.fl_str_mv Computational & Applied Mathematics - Sociedade Brasileira de Matemática Aplicada e Computacional (SBMAC)
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