Showing papers by "Mohamed Sahmoudi published in 2003"

Blind separation of instantaneous mixtures of impulsive stable sources

Abstract: This paper introduces a method of blind separation which extracts impulsive sources from their instantaneous mixtures. The "heavy-tailed", or "impulsive" signals are characterized by the nonexistence of the finite second (or higher) order moments. Such signals can be modeled by real-valued symmetric alpha-stable (SaS) processes. A novel blind source separation (BSS) algorithm for extracting "impulsive" source signals from their observed mixtures is presented. This algorithm is based on the minimum dispersion criterion. A new whitening procedure by the normalized covariance matrix is introduced and used as the first step of the algorithm. Some computer simulations are presented illustrating the performances of proposed method.

Estimation des signaux chirp multi-composantes affectés par un bruit impulsif α-stable

Abstract: In this paper we address the problem of parameter estimation of a chirp signal in impulsive noise environments. The first step of our estimation methods consists of transforming the problem to a problem of frequency estimation in -stable impulsive noise using a polynomial transformation. A high resolution method (MUSIC) is applied to the transformed signal for sinusoidal frequency estimation. Three approches are considered and compared in this work: (i) In the first one, we apply MUSIC to the truncated harmonic signal, (ii) in the second one, we apply MUSIC to the robust covariance estimate of the harmonic signal and (iii) in the third one, we apply MUSIC to the generalized covariation function of the signal.