A priori convergence of the Greedy algorithm for the parametrized reduced basis method
Buffa, Annalisa; Maday, Yvon; Patera, Anthony T.; Prud'Homme, Christophe; Turinici, Gabriel (2012), A priori convergence of the Greedy algorithm for the parametrized reduced basis method, Modélisation mathématique et analyse numérique, 46, 3, p. 595-603. http://dx.doi.org/10.1051/m2an/2011056
Type
Article accepté pour publication ou publiéDate
2012Nom de la revue
Modélisation mathématique et analyse numériqueVolume
46Numéro
3Éditeur
EDP Sciences
Pages
595-603
Identifiant publication
Métadonnées
Afficher la notice complèteRésumé (EN)
The convergence and efficiency of the reduced basis method used for the approximation of the solutions to a class of problems written as a parametrized PDE depends heavily on the choice of the elements that constitute the "reduced basis". The purpose of this paper is to analyze the a priori convergence for one of the approaches used for the selection of these elements, the greedy algorithm. Under natural hypothesis on the set of all solutions to the problem obtained when the parameter varies, we prove that three greedy algorithms converge; the last algorithm, based on the use of an a posteriori estimator, is the approach actually employed in the calculations.Mots-clés
reduced basis approximations; Greedy algorithm; a priori analysis; best fit analysisPublications associées
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