Seminar by Nezha Mamouni

Use of Copulas for Blind Source Separation of Independent/Dependent Sources

The problem of Blind Source Separation (BSS) consists in retrieving unobserved mixed signals from unknown mixtures of them, where there is no, or very limited, information about the source signals and/or the mixing system. In this thesis, we present algorithms in order to separate instantaneous and convolutive mixtures. The principle of these algorithms is to minimize, appropriate separation criteria based on copula densities, using descent gradient type algorithms. These methods can magnificently separate instantaneous and convolutive mixtures of possibly dependent source components even when the copula model is unknown.