Towards Adaptive Blind Extraction of Post-Nonlinearly Mixed Signals

A novel approach which extends blind source extraction (BSE) of one or group of sources to the case of post-nonlinear mixtures is proposed. This is achieved by an adaptive algorithm in which the cost function jointly estimates the kurtosis and a measure of nonlinearity. The analysis of both the quantitative and qualitative performance is provided, and simulation results are presented which illustrate the validity of the proposed approach.