Blind source separation by new M-WARP algorithm

A new independent component analysis technique is presented, which is based on the information-theoretic approach and implemented by the functional-link network, that allows mixed independent sub-Gaussian and super-Gaussian source signals to be separated out. To assess the theory, the results of computer simulations performed both on synthetic and real-world data are presented, and the performances of the new algorithm compared with those exhibited by the `mixture of densities´ based algorithm of Xu et al. [1997]