Two-stage neural network for blind sources separation

Abstract

In this paper, an on-line implementation of the simultaneous diagonalization (SD) of two different symmetric matrices is addressed. A two-stage neural network which consists of self-normalizing decorrelation and extended Oja's rule, is presented for an on-line implementation of SD. The SD of the 2nd- and 4th-order moment matrices is known as one solution to the blind sources separation problem. It will be shown that the two-stage network presented can recover the source signals from a linear mixture without the knowledge of the mixing matrix and the distribution of the source signals.