A regression model with a hidden logistic process for signal parametrization - Archive ouverte HAL Accéder directement au contenu
Communication Dans Un Congrès Année : 2009

A regression model with a hidden logistic process for signal parametrization

Résumé

A new approach for signal parametrization, which consists of a specific regression model incorporating a discrete hidden logistic process, is proposed. The model parameters are estimated by the maximum likelihood method performed by a dedicated Expectation Maximization (EM) algorithm. The parameters of the hidden logistic process, in the inner loop of the EM algorithm, are estimated using a multi-class Iterative Reweighted Least-Squares (IRLS) algorithm. An experimental study using simulated and real data reveals good performances of the proposed approach.
Fichier principal
Vignette du fichier
Chamroukhi_ESANN2009.pdf (209.84 Ko) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)
Loading...

Dates et versions

hal-00447806 , version 1 (15-01-2010)

Identifiants

  • HAL Id : hal-00447806 , version 1

Citer

Faicel Chamroukhi, Allou Samé, Gérard Govaert, Patrice Aknin. A regression model with a hidden logistic process for signal parametrization. 17th European Symposium on Artificial Neural Networks, Advances in Computational Intelligence and Learning, Apr 2009, Bruges, Belgium. pp.1-6. ⟨hal-00447806⟩
88 Consultations
61 Téléchargements

Partager

Gmail Facebook X LinkedIn More