On the Worst-Case Convergence of MR and CG for Symmetric Positive Definite Tridiagonal Toeplitz Matrices

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SYSNO ASEP	0031798
Document Type	J - Journal Article
R&D Document Type	Journal Article
Subsidiary J	Článek ve WOS
Title	On the Worst-Case Convergence of MR and CG for Symmetric Positive Definite Tridiagonal Toeplitz Matrices
Title	O nejhorší konvergenci MR a CG pro symetrické pozitivně definitní třídiagonální toeplitzovské matice
Author(s)	Liesen, J. (DE) Tichý, Petr (UIVT-O)_{SAI, RID, ORCID}
Source Title	Electronic Transactions on Numerical Analysis. - : Kent State University - ISSN 1068-9613 Roč. 20, - (2005), s. 180-197
Number of pages	18 s.
Language	eng - English
Country	US - United States
Keywords	Krylov subspace methods ; conjugate gradient method ; minimal residual method ; convergence analysis ; tridiagonal Toeplitz matrices ; Poisson equation
Subject RIV	BA - General Mathematics
R&D Projects	KJB1030306 GA AV ČR - Academy of Sciences of the Czech Republic (AV ČR)
CEZ	AV0Z10300504 - UIVT-O (2005-2011)
UT WOS	000234240200012
EID SCOPUS	29344432413
Annotation	For the considered model problems, we answer the questions how slow the convergence of the iterative solvers might possibly be, which initial vectors lead to the maximal convergence quantity in the next-to-last iteration step, and how much the convergence quantity in this case differs from an "average" case.
Workplace	Institute of Computer Science
Contact	Tereza Šírová, sirova@cs.cas.cz, Tel.: 266 053 800
Year of Publishing	2006

Number of the records: 1