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Blind source separation is a mature field of research with a broad range of applications, which is still a current topic. It is motivated by practical problems that involve several source signals and several sensors. Each sensor receives a mixture of the source signals. The problem under consideration consists of recovering the original waveforms of the source signals without any knowledge of the mixture structure. The latter may be instantaneous linear mixture, convolutive mixture or nonlinear mixture. This talk concentrates on Model driven approaches with some applications in various fields of engineering. A discussion on Data driven approaches versus Model driven ones will be provided.