Convergence estimates for multigrid algorithms

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dc.contributor.authorKang, KSko
dc.contributor.authorKwak, Do Youngko
dc.date.accessioned2011-01-07T06:29:06Z-
dc.date.available2011-01-07T06:29:06Z-
dc.date.created2012-02-06-
dc.date.created2012-02-06-
dc.date.issued1997-
dc.identifier.citationCOMPUTERS & MATHEMATICS WITH APPLICATIONS, v.34, pp.15 - 22-
dc.identifier.issn0898-1221-
dc.identifier.urihttp://hdl.handle.net/10203/21474-
dc.description.abstractTo estimate convergence of the multigrid algorithms, we need some assumptions on smoothers. The assumptions for typical smoothers are well analyzed in the multigrid literature [1,2]. However, numerical evidence shows that Kaczmarz smoother does not satisfy above assumptions. Thus, we introduce a weaker condition which is satisfied by Kaczmarz smoother as well as Jacobi and Gauss-Seidel smoother. Under these weaker assumptions, we show that the convergence factor of V-cycle multigrid algorithm is delta = 1-1/(C(j-1)). These assumptions for Kaczmarz smoother are verified by numerical experiment.-
dc.languageEnglish-
dc.language.isoen_USen
dc.publisherPERGAMON-ELSEVIER SCIENCE LTD-
dc.subjectV-CYCLE-
dc.titleConvergence estimates for multigrid algorithms-
dc.typeArticle-
dc.identifier.wosidA1997YF53700002-
dc.identifier.scopusid2-s2.0-0031272840-
dc.type.rimsART-
dc.citation.volume34-
dc.citation.beginningpage15-
dc.citation.endingpage22-
dc.citation.publicationnameCOMPUTERS & MATHEMATICS WITH APPLICATIONS-
dc.embargo.liftdate9999-12-31-
dc.embargo.terms9999-12-31-
dc.contributor.localauthorKwak, Do Young-
dc.contributor.nonIdAuthorKang, KS-
dc.type.journalArticleArticle-
dc.subject.keywordAuthormultigrid method-
dc.subject.keywordAuthorsmoothing assumptions-
dc.subject.keywordAuthorKaczmarz smoothing-
dc.subject.keywordPlusV-CYCLE-
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