Multichannel blind separation of sources algorithm based on cross-cumulant and the Levenberg-Marquardt method. - Archive ouverte HAL Accéder directement au contenu
Article Dans Une Revue IEEE Transactions on Signal Processing Année : 1999

Multichannel blind separation of sources algorithm based on cross-cumulant and the Levenberg-Marquardt method.

Résumé

The algorithms of blind separation of sources, in the general case and for instantaneous mixtures, are based on high-order statistics; most of them use the fourth-order statistics. For an instantaneous mixture of only two sources, we proposed in {mansour-ieee-95} an algorithm of blind separation of sources. The separation was achieved by minimizing the cross-cumulant (2x2) of the two output signals. The minimization of that cross-cumulant was achieved using a gradient algorithm. In this paper, we derive a new cost function which is more general than the first one, also based on the cross-cumulant (2x2) of the output signals. This new algorithm deals with Multiple Inputs and Multiple Outputs (MIMO) and uses a Levenberg-Marquardt method for the minimization of the cost function. The actual algorithm is very fast; the criterion convergence is attained in less than 50 iterations. In addition, it yields good results even in the case of about 300 signal samples. Good experimental results were obtained even with five stationary signals.
Fichier non déposé

Dates et versions

hal-00802439 , version 1 (19-03-2013)

Identifiants

  • HAL Id : hal-00802439 , version 1

Citer

Ali Mansour, Ohnishi Noboru. Multichannel blind separation of sources algorithm based on cross-cumulant and the Levenberg-Marquardt method.. IEEE Transactions on Signal Processing, 1999, 47 (11), pp.3172 - 3175. ⟨hal-00802439⟩
71 Consultations
0 Téléchargements

Partager

Gmail Mastodon Facebook X LinkedIn More