INDEPENDENT COMPONENT ANALYSIS AND BLIND SIGNAL SEPARATION: THEORY, ALGORITHMS AND APPLICATIONS

This paper reviews Independent Components Analysis (ICA) and Blind Signal Separation (BSS) problems. An overview on the main statistical principles that guide the search for the independent components is formulated, methods for blind signal separation that require both high-order and second-order statistics are also illustrated. Some of the most successful algorithms for both ICA and BSS are derived. Experimental applications in different signal processing tasks such as passive sonar, nondestructive ultrasound inspection and electrical-load time series are presented.