NEW MAXIMUM LIKELIHOOD ESTIMATION ALGORITHM FOR BLIND SEPARATION
Hongwei Li · Chinese Journal of Engineering Geophysics · 2004
Blind Source Separation (BSS) or Independent Component Analysis (ICA) are emerging techniques of array processing and data analysis, aiming at recovering unobserved signals from observed mixtures, exploiting only the assumption of mutual independence between the signals. It has become an increasing important research field due to its rapid growing applications in various areas, such as biomedical signal analysis, speech recognition, tele communication and so on. Based on the question about separating the arbitrary source signals, according to the Probability Density Function (PDF) of the observed signals and the separated signals, this paper chooses a nonlinear function with a parameter to be approximate to the PDF of super-Gaussian and sub-Gaussian sources, and then we can separate the sig nals. The effectiveness and performance of the algorithm are verified by the computer simu lations.