Please use this identifier to cite or link to this item: https://doi.org/10.15480/882.183
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dc.contributor.authorVoß, Heinrich-
dc.date.accessioned2006-03-01T16:34:13Zde_DE
dc.date.available2006-03-01T16:34:13Zde_DE
dc.date.issued2006-02-
dc.identifier.citationPreprint. Published in: Annals European Academy of Sciences 2005, 152-183 (2005)de_DE
dc.identifier.urihttp://tubdok.tub.tuhh.de/handle/11420/185-
dc.description.abstractThis paper surveys numerical methods for general sparse nonlinear eigenvalue problems with special emphasis on iterative projection methods like Jacobi–Davidson, Arnoldi or rational Krylov methods and the automated multi–level substructuring. We do not review the rich literature on polynomial eigenproblems which take advantage of a linearization of the problem.en
dc.language.isoende_DE
dc.relation.ispartofseriesPreprints des Institutes für Mathematik;Bericht 97-
dc.rightsinfo:eu-repo/semantics/openAccess-
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/
dc.subjectnonlinear eigenvalue problemde_DE
dc.subjectiterative projection methodde_DE
dc.subjectJacobi–Davidson methodde_DE
dc.subjectArnoldi methodde_DE
dc.subjectrational Krylov methodde_DE
dc.subject.ddc510: Mathematikde_DE
dc.titleProjection methods for nonlinear sparse eigenvalue problemsde_DE
dc.typeWorking Paperde_DE
dc.date.updated2006-03-01T16:34:15Zde_DE
dc.identifier.urnurn:nbn:de:gbv:830-opus-2476de_DE
dc.identifier.doi10.15480/882.183-
dc.type.diniworkingPaper-
dc.subject.ddccode510-
dc.subject.msc65F15:Eigenvalues, eigenvectorsen
dc.subject.msc35P30:Nonlinear eigenvalue problems, nonlinear spectral theory for PDOen
dc.subject.msccode35P30-
dc.subject.msccode65F15-
dcterms.DCMITypeText-
tuhh.identifier.urnurn:nbn:de:gbv:830-opus-2476de_DE
tuhh.publikation.typworkingPaperde_DE
tuhh.opus.id247de_DE
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dc.identifier.hdl11420/185-
tuhh.abstract.englishThis paper surveys numerical methods for general sparse nonlinear eigenvalue problems with special emphasis on iterative projection methods like Jacobi–Davidson, Arnoldi or rational Krylov methods and the automated multi–level substructuring. We do not review the rich literature on polynomial eigenproblems which take advantage of a linearization of the problem.de_DE
tuhh.publication.instituteMathematik E-10de_DE
tuhh.publication.instituteNumerische Simulation E-10 (H)de_DE
tuhh.identifier.doi10.15480/882.183-
tuhh.type.opusResearchPaper-
tuhh.institute.germanMathematik E-10de
tuhh.institute.englishMathematics E-10en
tuhh.institute.id47de_DE
tuhh.type.id17de_DE
tuhh.gvk.hasppnfalse-
tuhh.series.id20-
tuhh.series.namePreprints des Institutes für Mathematik-
dc.type.driverworkingPaper-
dc.identifier.oclc930767862-
dc.type.casraiWorking Paper-
tuhh.relation.ispartofseriesPreprints des Institutes für Mathematikde_DE
tuhh.relation.ispartofseriesnumber97de_DE
datacite.resourceTypeWorking Paper-
datacite.resourceTypeGeneralText-
item.grantfulltextopen-
item.openairecristypehttp://purl.org/coar/resource_type/c_8042-
item.creatorGNDVoß, Heinrich-
item.openairetypeWorking Paper-
item.tuhhseriesidPreprints des Institutes für Mathematik-
item.fulltextWith Fulltext-
item.cerifentitytypePublications-
item.creatorOrcidVoß, Heinrich-
item.languageiso639-1en-
item.seriesrefPreprints des Institutes für Mathematik;97-
item.mappedtypeWorking Paper-
crisitem.author.deptMathematik E-10-
crisitem.author.orcid0000-0003-2394-375X-
crisitem.author.parentorgStudiendekanat Elektrotechnik, Informatik und Mathematik-
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