Blind Separation Using Characteristic Function Based Criterion
Jenny Eriksson, Visa Koivunen · 2001
Abstract — We propose a novel method for blind separation of statistically independent sources. The objective function used in the separation is based on the fact that the joint characteristic function factors to a product of the characteristic functions of the in-dependent marginals. New algorithm for minimizing the above criterion is derived as well. It estimates the separating matrix by ensuring that the sources are pairwise independent. The theoretical character-istic functions in the objective function are replaced by their empirical counterparts. Simulation studies demonstrating the reliable performance of the pro-posed method in separating many different types of sources are presented. In particular, distributions of-ten encountered in wireless communication applica-tions are employed in the examples. I.