Source Separation Using Second

STATISTICS Ulf Lindgren, Henrik Sahlin and Holger Broman Department of Applied Electronics Chalmers University of Technology S-412 96 G oteborg, Sweden E-mail:[email protected], [email protected], [email protected] ABSTRACT It is often assumed that blind separation of dynamically mixed sources can not be accomplished with second order statistics. In this paper it is shown that separation of dynamically mixed sources indeed can be performed using second order statistics only. Two approaches to achieve this separation are presented. The rst approach is to use a new criterion, based on second order statistics. The criterion is used in order to derive a gradient based separation algorithm as well as a modi ed Newton separation algorithm. The uniqueness of the solution representing separation is also investigated. The other approach is to use System Identi cation. In this context system identi ability results are presented. Simulations using both the criterion based approach and a Recursive Prediction Error Method are also presented.