Issue |
ESAIM: ProcS
Volume 45, September 2014
Congrès SMAI 2013
|
|
---|---|---|
Page(s) | 148 - 157 | |
DOI | https://doi.org/10.1051/proc/201445015 | |
Published online | 13 November 2014 |
Convergence results on greedy algorithms for high-dimensional eigenvalue problems*
Université Paris Est, CERMICS, Projet
MICMAC, Ecole des Ponts ParisTech - INRIA, 6 & 8 avenue Blaise Pascal, 77455
Marne-la-Vallée Cedex 2,
France ;
ehrlachv@cermics.enpc.fr
In this paper, we present two greedy algorithms for the computation of the lowest eigenvalue (and an associated eigenvector) of a high-dimensional eigenvalue problem, which have been introduced and analyzed recently in a joint work with Eric Cancès and Tony Lelièvre [1]. The performance of our algorithms is illustrated on toy numerical test cases, and compared with that of another greedy algorithm for eigenvalue problems introduced by Ammar and Chinesta [13].
Résumé
Dans ce document, nous présentons deux algorithmes gloutons for le calcul de la plus petite valeur propre (et d’un vecteur propre associé) d’un problème aux valeurs propres en grande dimension, qui ont été récemment introduits et analysés dans un travail commun avec Eric Cancès et Tony Lelièvre [1]. Le comportement numérique de ces algorithmes est illustré sur de petits cas tests, et comparé à celui d’un autre algorithme glouton proposé antérieurement par Ammar et Chinesta [13].
© EDP Sciences, SMAI 2014
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.