Blind sources separation based on bilinear time-frequency representations: A performance analysis

In this communication, the problem of blind sources separation is considered. Many solutions have been brought to that problem, among which the method recently introduced in [1][2], that consists in joint-diagonalizing a combined set of “spatial t-ƒ distributions (stƒd)” matrices. In [4], we have introduced new criteria of selection of the t-ƒ points to use in the building of matrices sets to joint-diagonalize or to anti joint-diagonalize. As these criteria are no more sufficient in the noisy case, new constraints are introduced in the shape of thresholds (calculated both by Bayesian and Neyman-Pearson approaches) leading to new criteria of selection of the matrices sets. Performance studies on these new algorithms are proposed versus SNR and computer simulations are provided.