Tensor Decompositions, State of the Art and Applications

Abstract : In this paper, we present a partial survey of the tools borrowed from tensor algebra, which have been utilized recently in Statistics and Signal Processing. It is shown why the decompositions well known in linear algebra can hardly be extended to tensors. The concept of rank is itself difficult to define, and its calculation raises difficulties. Numerical algorithms have nevertheless been developed, and some are reported here, but their limitations are emphasized. These reports hopefully open research perspectives for enterprising readers.
Type de document :
Chapitre d'ouvrage
J. G. McWhirter and I. K. Proudler. Mathematics in Signal Processing V, Clarendon Press, Oxford, pp.1-24, 2002


https://hal.archives-ouvertes.fr/hal-00347139
Contributeur : Pierre Comon <>
Soumis le : dimanche 14 décembre 2008 - 18:29:00
Dernière modification le : vendredi 26 mars 2010 - 10:03:06
Document(s) archivé(s) le : mardi 8 juin 2010 - 17:06:13

Fichiers

comonMSP02.pdf
Fichiers produits par l'(les) auteur(s)

Identifiants

  • HAL Id : hal-00347139, version 1
  • ARXIV : 0905.0454

Collections

Citation

Pierre Comon. Tensor Decompositions, State of the Art and Applications. J. G. McWhirter and I. K. Proudler. Mathematics in Signal Processing V, Clarendon Press, Oxford, pp.1-24, 2002. <hal-00347139>

Exporter

Partager

Métriques

Consultations de
la notice

216

Téléchargements du document

177