An adaptive entropy optimization algorithm for blind source separation

Independent component analysis (ICA) or blind signal separation (BSS) has become an increasing important research field due to its rapidly growing applications in various areas, such as telecommunication systems, sonar and radar systems, audio and acoustics, image enhancement and biomedical signal processing. First, a novel adaptive ICA (AICA) entropy optimization algorithm for finding pairs of simplified activation functions (SAF) is introduced. Then, the theoretical explanation is described. Finally we discuss the algorithm with a few existing representative methods. Experimental simulation results prove that the algorithm is effective at separating signals.