Skip to Main content Skip to Navigation
Journal articles

A new method for interpolating in a convex subset of a Hilbert space

Abstract : In this paper, interpolating curve or surface with linear inequality constraints is considered as a general convex optimization problem in a Reproducing Kernel Hilbert Space. We propose a new approximation method based on a discretized optimization problem in a finite-dimensional Hilbert space under the same set of constraints. We prove that the approximate solution converges uniformly to the optimal constrained interpolating function. An algorithm is derived and numerical examples with boundedness and mono-tonicity constraints in one and two dimensions are given.
Document type :
Journal articles
Complete list of metadata

https://hal.archives-ouvertes.fr/hal-01136466
Contributor : Hassan Maatouk <>
Submitted on : Wednesday, December 30, 2015 - 10:11:58 AM
Last modification on : Monday, May 10, 2021 - 10:52:06 AM

File

Maatouk_H.pdf
Files produced by the author(s)

Identifiers

Citation

Xavier Bay, Laurence Grammont, Hassan Maatouk. A new method for interpolating in a convex subset of a Hilbert space. Computational Optimization and Applications, Springer Verlag, 2017, 68 (1), pp.95-120. ⟨10.1007/s10589-017-9906-9⟩. ⟨hal-01136466v2⟩

Share

Metrics

Record views

1166

Files downloads

944