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Titre: Blind source separation
Auteur(s): Bendermel, Qasem
Belouchrani, Mohamed Arezki Adel, Directeur de thèse
Adnane, M., Directeur de thèse
Mots-clés: Blind source separation
Independent Component Analysis
Signal process-ing
Date de publication: 2017
Résumé: Blind Source Separation (BSS) is a statistical approach to separating individual signals from an observed mixture of a group of signals. BSS relies on only very weak assumptions on the signals and the mixing process and this blindness enables the technique to be used in a wide variety of situations. Research in the field of Blind Source Separation has resulted in the development of a family of algorithms, known as Independent Component Analysis (ICA) algorithms, that can reliably and efficiently achieve blind separation of signals. There are two important problems that are generally considered: instantaneous BSS and convolutive BSS. The difference between these two is based on the nature of the signal mixing process. In this thesis, the mathematical foundations of both instanta-neous and convolutive BSS are developed. Once this mathematical framework has been established, the emphasis of the thesis moves to experimental results obtained with ICA techniques .
Description: Mémoire de Master : Electronique : Alger, Ecole Nationale Polytechnique : 2017
Collection(s) :Département Electronique

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