A regularization process to implement self-organizing neuronal networks

Frédéric Alexandre 1 Nicolas P. Rougier 1 Thierry Viéville 2
1 CORTEX - Neuromimetic intelligence
INRIA Lorraine, LORIA - Laboratoire Lorrain de Recherche en Informatique et ses Applications
2 ODYSSEE - Computer and biological vision
DI-ENS - Département d'informatique de l'École normale supérieure, CRISAM - Inria Sophia Antipolis - Méditerranée , ENS Paris - École normale supérieure - Paris, Inria Paris-Rocquencourt, ENPC - École des Ponts ParisTech
Abstract : Kohonen Self-Organizing maps are interesting computational structures because of their original properties, including adaptive topology and competition, their biological plausibility and their successful applications to a variety of real-world applications. In this paper, this neuronal model is presented, together with its possible implementation with a variational approach. We then explain why, beyond the interest for understanding the visual cortex, this approach is also interesting for making easier and more efficient the choice of this neuronal technique for real-world applications.
Type de document :
Communication dans un congrès
International Conference on Engineering and Mathematics - ENMA 2006, Jul 2006, Bilbao/Spain, 2006
Liste complète des métadonnées

Littérature citée [15 références]  Voir  Masquer  Télécharger

https://hal.inria.fr/inria-00103256
Contributeur : Frédéric Alexandre <>
Soumis le : mardi 3 octobre 2006 - 17:37:53
Dernière modification le : vendredi 25 mai 2018 - 12:02:04
Document(s) archivé(s) le : mardi 6 avril 2010 - 17:54:11

Identifiants

  • HAL Id : inria-00103256, version 1

Citation

Frédéric Alexandre, Nicolas P. Rougier, Thierry Viéville. A regularization process to implement self-organizing neuronal networks. International Conference on Engineering and Mathematics - ENMA 2006, Jul 2006, Bilbao/Spain, 2006. 〈inria-00103256〉

Partager

Métriques

Consultations de la notice

351

Téléchargements de fichiers

206