Saloua Rhioui

Learn More
This paper deals with the problem of source separation in the case when the observations result from a multiple-input multiple-output convolutive mixing system. In a blind framework, higher order contrast functions have been proved to be efficient for extracting sources. Inspired by a semiblind approach, we propose new contrast functions for blind signal(More)
In this communication, we propose a new method to blindly identify the mixing matrix of a possibly underdetermined mixture of sources when input signals are cyclostationary with unknown cyclic frequencies. It relies upon a particular linear operator applied to the observations correlation matrix. Then, taking advantage of the properties of the above(More)
In this communication, we propose a new method to blindly identify the mixing matrix of a possibly under-determined mixture of cyclostationary source signals. It is based on the use of a linear operator applied on the observations correlation matrix. Exploiting the properties of the above transformed matrix, a set of cyclic frequencies is first estimated.(More)
This article addresses the problem of the blind identification of the mixing matrix in the case of a possibly under-determined instantaneous linear mixture of sources. The considered input signals are cyclo-stationary processes with unknown cyclic frequencies. We propose a new method consisting of the application of a particular linear operator on the(More)
This paper considers the problem of blind separation of a MIMO convolutive mixture of i.i.d. source signals. Separation criteria are considered for the overall extraction of source signals according to the use of so-called reference signals. We present a new MIMO contrast function using reference signals, which is moreover seen to have joint-diagonalization(More)
  • 1