ABSTRACT In this paper the blind equalization method of Tong, Xu and Kailath, which was derived under the assumption of a white transmitted sequence, is generalized in order to include correlated sources. The resulting algorithm can be applied to arbitrarily colored sources, assuming that the source second-order statistics are known. Because it makes explicit use of this information, the new al...

This paper studies the blind source separation (BSS) problem with the assumption that the source signals are cyclostationary. Identifiability and separability criteria based on second-order cyclostationary statistics (SOCS) alone are derived. The identifiability condition is used to define an appropriate contrast function. An iterative algorithm (ATH2) is derived to minimize this contrast funct...

Most second-order moment-based blind channel estimators belong to two categories: i) optimal correlation/spectral fitting techniques and ii) eigenstructure-based techniques. These two classes of algorithms have complementary advantages and disadvantages. In this paper, a new optimization criterion referred to as the joint optimization with subspace constraints (JOSC) is proposed to unify the tw...

This paper addresses the blind equalization problem for single-input multiple-output nonlinear channels, based on the second-order statistics (SOS) of the received signal. We consider the class of “linear in the parameters” channels, which can be seen as multiple-input systems in which the additional inputs are nonlinear functions of the signal of interest. These models include (but are not lim...

In the signal processing area, blind source separation (BSS) is a method aiming to recover independent sources from their linear instantaneous mixtures without resorting to any prior knowledge, such as mixing matrices and sources. There have been increased attentions given to blind source separation in many areas, including wireless communication, biomedical imaging processing, multi-microphone...

In the present paper a Multi Input Multi Output (MIMO) source separation method for dynamic channels is proposed. The algorithm is based on second order statistics of the observed signals. A new separation structure, based on cofactors, is proposed with a parametrization such as to reduce the number of estimated parameters to a minimum. Simulations with the algorithm are presented.

This paper describes a computationally simple method to perform text independent speaker verification using second order statistics. The suggested method, called Utterance Level Scoring (ULS), allows obtaining a normalized score using a single pass through the frames of the tested utterance. The utterance sample covariance is first calculated and then compared to the speaker covariance using a ...