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Multiscale approximation and reproducing kernel Hilbert space methods

dc.contributor.authorGriebel, Michael
dc.contributor.authorRieger, Christian
dc.contributor.authorZwicknagl, Barbara
dc.date.accessioned2024-08-23T07:14:18Z
dc.date.available2024-08-23T07:14:18Z
dc.date.issued2013
dc.identifier.urihttps://hdl.handle.net/20.500.11811/11928
dc.description.abstractWe consider reproducing kernels K : Ω x Ω → ℝ in multiscale series expansion form, i.e., kernels of the form K (x, y) = ∑ℓ∈ℕλjIΦ(x)Φ(y) with weights λ and structurally simple basis functions {Φℓ,i}. Here, we deal with basis functions such as polynomials or frame systems, where, for ℓ ∈ ℕ, the index set I is finite or countable. We derive relations between approximation properties of spaces based on basis functions {Φℓ,j : 1 ≤ ℓ ≤ L,jIj} and spaces spanned by translates of the kernel span{K(x1,·), . . . , K(xN,·)} with XN := {x1, . . . ,XN } ⊂ Ω if the truncation index L is appropriately coupled to the discrete set XN . An analysis of a numerically feasible approximation from trial spaces span{KL(x1,·), . . . , KL(xN,·)} based on finitely truncated series kernels of the form KL (x, y) := ∑L=1λjIΦ(x)Φ(y) is provided where the truncation index L is chosen sufficiently large depending on the point set XN . Furthermore, Bernstein-type inverse estimates and derivative-free sampling inequalities for kernel based spaces are obtained from estimates for spaces based on the basis functions {Φℓ,j : 1 ≤ ℓ ≤ L,jIj}.en
dc.format.extent22
dc.language.isoeng
dc.relation.ispartofseriesINS Preprints ; 1312
dc.rightsIn Copyright
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/
dc.subjectReproducing kernel Hilbert spaces
dc.subjectmultiscale expansion
dc.subjecta priori error estimates
dc.subjectBernstein estimates
dc.subject.ddc510 Mathematik
dc.subject.ddc518 Numerische Analysis
dc.titleMultiscale approximation and reproducing kernel Hilbert space methods
dc.typePreprint
dc.publisher.nameInstitut für Numerische Simulation (INS)
dc.publisher.locationBonn
dc.rights.accessRightsopenAccess
dc.relation.doihttps://doi.org/10.1137/130932144
ulbbn.pubtypeZweitveröffentlichung
dcterms.bibliographicCitation.urlhttps://ins.uni-bonn.de/publication/preprints


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