Abstract. We address the blind separation of two source signals from two real-valued instantaneous linear mixtures. Appropriate weighting of previous estimation expressions yields a family of closed-form estimators of the separation parameter which are consistent under rather general conditions. The weight coefficient for the asymptotically (large-sample) most efficient estimator of the family, i.e., the estimator with optimal finite-sample performance, is obtained as a function of the source statistics. Experimental results demonstrate the benefits of the optimal weighted estimator.
International audienceThis contribution contains a theoretical analysis on asymptotic stability requ...
In this paper, blind source separation is discussed with more sources than mixtures. This blind sepa...
In this paper, blind source separation is discussed with more sources than mixtures. This blind sepa...
Blind source separation aims to extract a set of independent signals from a set of observed linear m...
In this thesis, we focus on the signal processing foundations of this emerging field of fundamental ...
Abstract—An important problem in the field of blind source separation (BSS) of real convolutive mixt...
ABSTRACT We present a new approach to the blind source separation problem (BSS, also known as Indepe...
Abstract—Blind source separation (BSS) aims to recover a set of statistically independent source sig...
The semiparametric statistical model is used to formulate the problem of blind source separation. Th...
In this paper, we propose a new semi-parametric approach for blind source separation (BSS) of noisy ...
International audienceWe propose two methods for separating mixture of independent sources without a...
Algorithms for the blind separation of sources can be derived from several different principles. Thi...
Most source separation algorithms are based on a model of stationary sources. However, it is a simpl...
Abstract—This letter presents a new maximum likelihood method for blindly separating linear instanta...
We propose a novel blind source separation algorithm called Block AutoRegressive Blind Identificatio...
International audienceThis contribution contains a theoretical analysis on asymptotic stability requ...
In this paper, blind source separation is discussed with more sources than mixtures. This blind sepa...
In this paper, blind source separation is discussed with more sources than mixtures. This blind sepa...
Blind source separation aims to extract a set of independent signals from a set of observed linear m...
In this thesis, we focus on the signal processing foundations of this emerging field of fundamental ...
Abstract—An important problem in the field of blind source separation (BSS) of real convolutive mixt...
ABSTRACT We present a new approach to the blind source separation problem (BSS, also known as Indepe...
Abstract—Blind source separation (BSS) aims to recover a set of statistically independent source sig...
The semiparametric statistical model is used to formulate the problem of blind source separation. Th...
In this paper, we propose a new semi-parametric approach for blind source separation (BSS) of noisy ...
International audienceWe propose two methods for separating mixture of independent sources without a...
Algorithms for the blind separation of sources can be derived from several different principles. Thi...
Most source separation algorithms are based on a model of stationary sources. However, it is a simpl...
Abstract—This letter presents a new maximum likelihood method for blindly separating linear instanta...
We propose a novel blind source separation algorithm called Block AutoRegressive Blind Identificatio...
International audienceThis contribution contains a theoretical analysis on asymptotic stability requ...
In this paper, blind source separation is discussed with more sources than mixtures. This blind sepa...
In this paper, blind source separation is discussed with more sources than mixtures. This blind sepa...