Blind Separation Using Characteristic Function Based Criterion

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 independent 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 characteristic functions in the objective function are replaced by their empirical counterparts. Simulation studies demonstrating the reliable performance of the proposed method in separating many different types of sources are presented. In particular, distributions often encountered in wireless communication applications are employed in the examples.