Blind Source Separation Algorithm Based on Maximum Signal Noise Ratio

Abstract

A low computational complexity instantaneous linear mixture signals blind separation algorithm was proposed, which is based on the character that Signal Noise Ratio (SNR) is maximal when statistically independent source signals are completely separated, and it is used as a separation contrast. Source signals are replaced by moving average of estimate signals. The function of covariance matrixes of the source signals and noises was expressed by the generalized eigenvalue (GE) problem, and unmixing matrix was achieved by solving the generalized eigenvalue problem without any iterative. Compared to the typical information-theoretical approaches, the merit of this algorithm is effectively and low complexity in computation.