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Open Access Green möglich sobald Postprint bei der ZB eingereicht worden ist.
Error estimates for approximate operator inversion via Kernel-based methods.
Lect. Notes Comput. Sc. 9213, 399-413 (2015)
In this paper we investigate error estimates for the approximate solution of operator equations Af = u, where u needs not to be a function on the same domain as f. We use the well-established theory of generalized interpolation, also known as optimal recovery in reproducing kernel Hilbert spaces, to generate an approximation to f from finitely many samples u(x1),…, u(xN). To derive error estimates for this approximation process we will show sampling inequalities on fairly general Riemannian manifolds.
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Publikationstyp
Artikel: Journalartikel
Dokumenttyp
Wissenschaftlicher Artikel
Schlagwörter
Generalized Interpolation ; Positive Definite Functions ; Reproducing Kernel Hilbert Spaces ; Sampling Inequalities On Manifolds
ISSN (print) / ISBN
0302-9743
e-ISSN
1611-3349
Konferenztitel
8th International Conference on Curves and Surfaces
Konferzenzdatum
12-18 June 2014
Konferenzort
Paris, France
Zeitschrift
Lecture Notes in Computer Science
Quellenangaben
Band: 9213,
Seiten: 399-413
Verlag
Springer
Verlagsort
Berlin [u.a.]
Institut(e)
Institute of Computational Biology (ICB)