A priori convergence of the Generalized Empirical Interpolation Method.Report as inadecuate

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1 LJLL - Laboratoire Jacques-Louis Lions 2 DAM - Division of Applied Mathematics 3 IUF - Institut Universitaire de France 4 LLPR - Laboratoire de Logiciels pour la Physique des Réacteurs DM2S - Département de Modélisation des Systèmes et Structures : DEN-DM2S-SERMA-LLPR 5 CEREMADE - CEntre de REcherches en MAthématiques de la DEcision

Abstract : In an effort to extend the classical lagrangian interpolation tools, new interpolating methods that use general interpolating functions are explored. The Generalized Empirical Interpolation Method GEIM belongs to this class of new techniques. It generalizes the plain Empirical Interpolation Method by replacing the evaluation at interpolating points by application of a class of interpolating linear functions. Since its efficiency depends critically on the choice of the interpolating functions that are chosen by a Greedy selection procedure, the purpose of this paper is therefore to provide a priori convergence rates for the Greedy algorithm that is used to build the GEIM interpolating spaces.

Keywords : interpolation empirical interpolation EIM GEIM reduced basis

Author: Yvon Maday - Olga Mula - Gabriel Turinici -

Source: https://hal.archives-ouvertes.fr/


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