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Conference Paper: Preconditioned iterative methods for weighted toeplitz least squares problems

TitlePreconditioned iterative methods for weighted toeplitz least squares problems
Authors
Benzi, MicheleNg, Michael K.
KeywordsImage restoration
Augmented matrix
Constraint preconditioning
Splittings
Eigenvalue bounds
Iterative methods
Preconditioning
Issue Date2006
Citation
SIAM Journal on Matrix Analysis and Applications, 2006, v. 27, n. 4, p. 1106-1124 How to Cite?
DOI: http://dx.doi.org/10.1137/040616048
AbstractWe consider the iterative solution of weighted Toeplitz least squares problems. Our approach is based on an augmented system formulation. We focus our attention on two types of preconditioners: a variant of constraint preconditioning, and the Hermitian/skew-Hermitian splitting (HSS) preconditioner. Bounds on the eigenvalues of the preconditioned matrices are given in terms of problem and algorithmic parameters, and numerical experiments are used to illustrate the performance of the preconditioners. © 2006 Society for Industrial and Applied Mathematics.
Persistent Identifierhttp://hdl.handle.net/10722/276796
ISSN
0895-4798
2023 Impact Factor: 1.5
2023 SCImago Journal Rankings: 1.042
ISI Accession Number ID
WOS:000236099100012

 

DC FieldValueLanguage
dc.contributor.authorBenzi, Michele-
dc.contributor.authorNg, Michael K.-
dc.date.accessioned2019-09-18T08:34:41Z-
dc.date.available2019-09-18T08:34:41Z-
dc.date.issued2006-
dc.identifier.citationSIAM Journal on Matrix Analysis and Applications, 2006, v. 27, n. 4, p. 1106-1124-
dc.identifier.issn0895-4798-
dc.identifier.urihttp://hdl.handle.net/10722/276796-
dc.description.abstractWe consider the iterative solution of weighted Toeplitz least squares problems. Our approach is based on an augmented system formulation. We focus our attention on two types of preconditioners: a variant of constraint preconditioning, and the Hermitian/skew-Hermitian splitting (HSS) preconditioner. Bounds on the eigenvalues of the preconditioned matrices are given in terms of problem and algorithmic parameters, and numerical experiments are used to illustrate the performance of the preconditioners. © 2006 Society for Industrial and Applied Mathematics.-
dc.languageeng-
dc.relation.ispartofSIAM Journal on Matrix Analysis and Applications-
dc.subjectImage restoration-
dc.subjectAugmented matrix-
dc.subjectConstraint preconditioning-
dc.subjectSplittings-
dc.subjectEigenvalue bounds-
dc.subjectIterative methods-
dc.subjectPreconditioning-
dc.titlePreconditioned iterative methods for weighted toeplitz least squares problems-
dc.typeConference_Paper-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1137/040616048-
dc.identifier.scopuseid_2-s2.0-33750169124-
dc.identifier.volume27-
dc.identifier.issue4-
dc.identifier.spage1106-
dc.identifier.epage1124-
dc.identifier.eissn1095-7162-
dc.identifier.isiWOS:000236099100012-
dc.identifier.issnl0895-4798-

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