Convolutive blind signal separation via polynomial matrix generalised eigenvalue decomposition
Soydan Redif · Electronics Letters · 2016
An extension of the generalised eigenvalue decomposition (GEVD) to polynomial matrices, that is, a polynomial GEVD is proposed. A method for its application to convolutive blind signal separation is then introduced. The author shows that the source signals can be estimated using two related, but different, ‘target’ polynomial matrices. These polynomial matrices are parahermitian matrices, corresponding to two different signal time intervals, which capture the non‐stationarity of the sources. The validity of our method in separating the sources from their convolutive mixtures is demonstrated with computer simulations.