Title :
Adaptive blind separation of independent sources: a second-order stable algorithm for the general case
Author :
Delfosse, Nathalie ; Loubaton, Philippe
Author_Institution :
Lille I Univ., Villeneuve d´´Ascq, France
fDate :
7/1/2000 12:00:00 AM
Abstract :
In this paper, the adaptive separation of convolutive mixtures of independent sources is addressed. The case where the number of sensors is strictly greater than the number of sources is considered. Under a mild assumption on the unknown transfer function, it is shown that the separation can be nearly achieved by a three-step procedure: a linear prediction algorithm in the singular case; a separation of an instantaneous mixture; and the implementation of the inverse of the prediction filter. The main difficulty of this approach is to control the stability of this IIR filter. For that purpose, we use a normalized lattice structure, which is stable for any choice of its parameters
Keywords :
IIR filters; adaptive filters; adaptive signal processing; filtering theory; lattice filters; prediction theory; stability; IIR filter stability; adaptive blind separation; convolutive mixtures; general case; independent sources; instantaneous mixture separation; linear prediction algorithm; normalized lattice structure; prediction filter inverse; second-order stable algorithm; singular case; three-step procedure; Adaptive filters; Finite impulse response filter; IIR filters; Lattices; Nonlinear filters; Prediction algorithms; Signal processing; Source separation; Stability; Transfer functions;
Journal_Title :
Circuits and Systems I: Fundamental Theory and Applications, IEEE Transactions on
