International audienceIn this paper, we study the blind separation of mixtures of propagating waves (delayed sources) encountered for example in underwater telephone (UWT) systems. We suggest a new second-order statistics method using as many observations as sources. First, we show that each of the N delayed sources can be developed as a particular linear combination of the different temporal-derivatives of the N observations. Under some assumptions, an instantaneous rectangular separating matrix is then identified by the joint diagonalization of a set of covariance matrices estimated from the observations and its derivatives. The algorithm used takes into account the particular structure of the spectral mixing matrix encountered. A numeric...
The ultimate goal of instantaneous blind signal extraction is to find one source out of an instantan...
International audienceThis paper is a contribution to the problem of the separation of propagating s...
In this paper, we introduce new time-varying fractional spec-tral matrices to exploit both the nonst...
International audienceIn this paper, we study the blind separation of mixtures of propagating waves ...
The problem of separating n linearly superimposed uncorrelated signals and determing their mixing co...
International audienceThis paper is concerned with the problem of blind separation of instantaneous ...
International audienceBecause it can be found in many applications, the Blind Separation of Sources ...
We introduce a novel approach suitable for blind separation of convolutive Multiple-Input-Multiple-O...
The separation of two unknown signals that mixed together in an unknown manner was shown to be possi...
International audienceIn the last decade, many researchers have investigated the blind separation of...
International audienceFor the last 10 years, source separation has raised an increasing interest, pa...
In this thesis, we focus on the signal processing foundations of this emerging field of fundamental ...
Unlike conventional blind source separation (BSS) deals with independent identically distributed (i....
International audienceThis paper focuses on the blind separation of stationary colored sources using...
International audienceThis paper focuses on the blind separation of stationary colored sources using...
The ultimate goal of instantaneous blind signal extraction is to find one source out of an instantan...
International audienceThis paper is a contribution to the problem of the separation of propagating s...
In this paper, we introduce new time-varying fractional spec-tral matrices to exploit both the nonst...
International audienceIn this paper, we study the blind separation of mixtures of propagating waves ...
The problem of separating n linearly superimposed uncorrelated signals and determing their mixing co...
International audienceThis paper is concerned with the problem of blind separation of instantaneous ...
International audienceBecause it can be found in many applications, the Blind Separation of Sources ...
We introduce a novel approach suitable for blind separation of convolutive Multiple-Input-Multiple-O...
The separation of two unknown signals that mixed together in an unknown manner was shown to be possi...
International audienceIn the last decade, many researchers have investigated the blind separation of...
International audienceFor the last 10 years, source separation has raised an increasing interest, pa...
In this thesis, we focus on the signal processing foundations of this emerging field of fundamental ...
Unlike conventional blind source separation (BSS) deals with independent identically distributed (i....
International audienceThis paper focuses on the blind separation of stationary colored sources using...
International audienceThis paper focuses on the blind separation of stationary colored sources using...
The ultimate goal of instantaneous blind signal extraction is to find one source out of an instantan...
International audienceThis paper is a contribution to the problem of the separation of propagating s...
In this paper, we introduce new time-varying fractional spec-tral matrices to exploit both the nonst...