Fourth-Order CONFAC Decomposition Approach for Blind Identification of UnderDetermined Mixtures - CICS Accéder directement au contenu
Communication Dans Un Congrès Année : 2012

Fourth-Order CONFAC Decomposition Approach for Blind Identification of UnderDetermined Mixtures

Résumé

We have recently proposed a second-order method for the blind identification of underdetermined mixtures that relies on the constrained factor (CONFAC) decomposition. It consists in storing successive second-order derivatives of the cumulant generating function (CGF) of the observations computed at different points of the observation space in a third-order tensor following a CONFAC model. In this work, we extend this approach to the case of third-order derivatives by resorting to a fourth-order CONFAC decomposition. We show how different third-order derivative types can be combined into a single fourth-order CONFAC tensor model with the goal of increasing the diversity of observations, so that higher under-determinacy levels can be handled. Computer simulation results illustrate the performance of a CONFAC-based blind identification algorithm compared to some competing methods.
Fichier principal
Vignette du fichier
AlmeLC12-Bucarest.pdf (122.63 Ko) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)
Loading...

Dates et versions

hal-00725297 , version 1 (24-08-2012)

Identifiants

  • HAL Id : hal-00725297 , version 1

Citer

André L. F. de Almeida, Xavier Luciani, Pierre Comon. Fourth-Order CONFAC Decomposition Approach for Blind Identification of UnderDetermined Mixtures. EUSIPCO 2012 - 20th European Signal Processing Conference, Aug 2012, Bucarest, Romania. pp.1-5. ⟨hal-00725297⟩
260 Consultations
125 Téléchargements

Partager

Gmail Facebook X LinkedIn More