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

SYSNO ASEP	0404252
Document Type	J - Journal Article
R&D Document Type	Journal Article
Subsidiary J	Článek ve WOS
Title	By 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 Title	Numerical Algorithms. - : Springer - ISSN 1017-1398 Roč. 27, - (2001), s. 189-213
Number of pages	25 s.
Language	eng - English
Country	NL - Netherlands
Keywords	system 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 RIV	BA - General Mathematics
R&D Projects	GA201/98/P108 GA ČR - Czech Science Foundation (CSF)
CEZ	1030915
UT WOS	000172675300005
EID SCOPUS	0035602327
DOI	10.1023/A:1011889705659
Annotation	We 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.
Workplace	Institute of Computer Science
Contact	Tereza Šírová, sirova@cs.cas.cz, Tel.: 266 053 800
Year of Publishing	2002

Number of the records: 1