Blind extraction of singularly mixed source signals
Jozef M. Zurada, Jun Wang, Yuanqing Li · IEEE Transactions on Neural Networks · 2000
This paper introduces a novel technique for sequential blind extraction of singularly mixed sources. First, a neural-network model and an adaptive algorithm for single-source blind extraction are introduced. Next, extractability analysis is presented for singular mixing matrix, and two sets of necessary and sufficient extractability conditions are derived. The adaptive algorithm and neural-network model for sequential blind extraction are then presented. The stability of the algorithm is discussed. Simulation results are presented to illustrate the validity of the adaptive algorithm and the stability analysis. The proposed algorithm is suitable for the case of nonsingular mixing matrix as well as for singular mixing matrix.