BLIND SEPARATION OF CONVOLUTIVE MIXTURES USING NONSTATIONARITY AND FRACTIONAL LOWER ORDER STATISTICS (FLOS): APPLICATION TO AUDIO SIGNALS

In this paper, we introduce new time-varying fractional spec-tral matrices to exploit both the nonstationarity and heavy-tailed sources properties for blind separation of convolutive audio mixtures. We define these spectrum matrices, that are different for various delays, using fractional lower order sta-tistics (FLOS) of data. Similar to the second order statistics (SOS) based approaches, we maximize the sources inde-pendence by jointly diagonalizing these fractional matrices spectrum of the reconstructed signals using a mutual infor-mation criterion. A set of experiments using audio signals and real impulse response of acoustic room are designed to verify the usefulness of the proposed method. 1