Communication Dans Un Congrès Année : 2010

System identification under non-negativity constraints

Résumé

Dynamic system modeling plays a crucial role in the development of techniques for stationary and non-stationary signal processing. Due to the inherent physical characteristics of systems usually under investigation, non-negativity is a desired constraint that can be imposed on the parameters to estimate. In this paper, we propose a general method for system identification under non-negativity constraints. We derive additive and multiplicative weight update algorithms, based on (stochastic) gradient descent of mean-square error or Kullback-Leibler divergence. Experiments are conducted to validate the proposed approach.

Fichier principal
Vignette du fichier
paper.pdf (400.14 Ko) Télécharger le fichier
Origine Fichiers produits par l'(les) auteur(s)
Licence
Loading...

Dates et versions

hal-02111262 , version 1 (25-04-2019)

Licence

Identifiants

  • HAL Id : hal-02111262 , version 1

Citer

Jie Chen, Cédric Richard, Paul Honeine, Henri Lantéri, Céline Theys. System identification under non-negativity constraints. European Signal Processing Conference, Aug 2010, Aalborg, Denmark. pp.1728-1732. ⟨hal-02111262⟩
308 Consultations
264 Téléchargements

Partager

  • More