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By how much can Residual Minimization Accelerate the Convergence of Orthogonal Residual Methods?

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    SYSNO ASEP0404252
    Document TypeJ - Journal Article
    R&D Document TypeJournal Article
    Subsidiary JČlánek ve WOS
    TitleBy how much can Residual Minimization Accelerate the Convergence of Orthogonal Residual Methods?
    Author(s) Gutknecht, M. H. (CH)
    Rozložník, Miroslav (UIVT-O) SAI, RID, ORCID
    Source TitleNumerical Algorithms - ISSN 1017-1398
    Roč. 27, - (2001), s. 189-213
    Number of pages25 s.
    Languageeng - English
    CountryNL - Netherlands
    Keywordssystem of linear algebraic equations ; iterative method ; Krylov space method ; conjugate gradient method ; biconjugate gradient method ; CG ; CGNE ; CGNR ; CGS ; FOM ; GMRes ; QMR ; TFQMR ; residual smoothing ; MR smoothing ; QMR smoothing
    Subject RIVBA - General Mathematics
    R&D ProjectsGA201/98/P108 GA ČR - Czech Science Foundation (CSF)
    CEZ1030915
    UT WOS000172675300005
    EID SCOPUS0035602327
    DOI10.1023/A:1011889705659
    AnnotationWe estimate how much smaller the residuals or quasi-residuals of the minimizing methods can be compared to those of the corresponding Galerkin or Petrov-Galerkin method. By an interpretation of smoothing processes in coordinate space we deepen the understanding of some of the underlying relationships and introduce a unifying framework for minimal residual and quasi-residual smoothing.
    WorkplaceInstitute of Computer Science
    ContactTereza Šírová, sirova@cs.cas.cz, Tel.: 266 053 800
    Year of Publishing2002