FLEXIBLE ICA APPROACH TO THE NONLINEAR BLIND SIGNAL SEPARATION IN THE COMPLEX DOMAIN

This paper introduces an Independent Component Analysis (ICA) approach to the separation of nonlinear mixtures in the complex domain. Source separation is performed by a complex INFOMAX approach. Nonlinear complex functions involved in the processing are realized by pairs of spline neurons called “splitting functions”, working on the real and the imaginary part of the signal respectively. A simple adaptation algorithm is derived and some experimental re-sults that demonstrate the effectiveness of the proposed method are shown. 1. INTRODUCTITON In the last years Blind Source Separation (BSS) realized through Independent Component Analysis (ICA) have raised great interest in the signal processing community (see e.g