Preconditioners for low order thin plate spline approximations

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dc.contributor.authorStals, Linda
dc.contributor.authorRoberts, Stephen
dc.date.accessioned2015-12-08T22:13:54Z
dc.date.issued2008
dc.date.updated2016-02-24T10:35:13Z
dc.description.abstractA commonly used method for fitting smooth functions to noisy data is the thin-plate spline method. Traditional thin-plate splines use radial basis functions and consequently require the solution of a dense linear system of equations whose dimension grows
dc.identifier.isbn9783540751991
dc.identifier.urihttp://hdl.handle.net/1885/29999
dc.publisherSpringer
dc.relation.ispartofDomain Decomposition Methods in Science and Engineering XVII
dc.relation.isversionof1st Edition
dc.subjectKeywords: Basis functions; Finite element grid; Ill-conditioned; Iterative solvers; Linear system of equations; Low order; Low-order polynomials; Noisy data; Number of datum; Preconditioner; Preconditioners; Radial basis functions; Regularisation; Schwarz method; S
dc.titlePreconditioners for low order thin plate spline approximations
dc.typeBook chapter
local.bibliographicCitation.lastpage646
local.bibliographicCitation.placeofpublicationGermany
local.bibliographicCitation.startpage639
local.contributor.affiliationStals, Linda, College of Physical and Mathematical Sciences, ANU
local.contributor.affiliationRoberts, Stephen, College of Physical and Mathematical Sciences, ANU
local.contributor.authoruidStals, Linda, u4042952
local.contributor.authoruidRoberts, Stephen, u8602296
local.description.embargo2037-12-31
local.description.notesImported from ARIES
local.identifier.absfor010301 - Numerical Analysis
local.identifier.ariespublicationu4085724xPUB70
local.identifier.doi10.1007/978-3-540-75199-1_80
local.identifier.scopusID2-s2.0-78651541829
local.type.statusPublished Version

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