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The paper deals with the problem of blind source separation after a MIMO convolutive mixture. We propose an algorithm for the simultaneous extraction of all the sources. It is based on the PARAFAC decomposition of a tensor built from the observations and from so called reference signals. In particular this algorithm allows to overcome the classical drawbacks of the deflation approach in the sequential...
This correspondence deals with the problem of source separation in the case where the output of a multivariate convolutive mixture is observed: we propose novel and generalized conditions for the blind identifiability of a separating system. The results are based on higher-order statistics and are valid in the case of stationary but not necessarily i.i.d. signals. In particular, we extend recent results...
In this communication, we address the problem of the blind separation of convolutive mixtures of sources also known as blind equalization of linear time invariant multi-input multi- output systems in digital communications. The considered input signals are cyclo-stationary processes whose cyclic frequencies are not necessarily known. We propose a new method which, by some aspects, generalizes previous...
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