A flexible Blind source recovery in complex nonlinear environment
Daniele Vigliano, Michele Scarpiniti, Raffaele Parisi, Aurelio Uncini · 2006
In this paper the source recovery of nonlinear mixtures in the complex domain is addressed by an independent component analysis (ICA) approach. Extending the well-known real PNL mixtures, source recovery is performed by a complex INFOMAX approach. Nonlinear complex functions involved in the learning process 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 results that demonstrate the effectiveness of the proposed method are shown