Title :
Blind extraction of singularly mixed source signals
Author :
Li, Yuanqing ; Wang, Jun ; Zurada, Jacek M.
Author_Institution :
Dept. of Autom. Control Eng., South China Univ. of Technol., Guangzhou, China
fDate :
11/1/2000 12:00:00 AM
Abstract :
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, an 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.
Keywords :
adaptive signal detection; matrix algebra; neural nets; stability; adaptive algorithm; extractability analysis; neural-network model; sequential blind extraction; singular matrix; singularly mixed source signals; stability; Adaptive algorithm; Analytical models; Biomedical signal processing; Blind equalizers; Blind source separation; Image restoration; Independent component analysis; Signal processing algorithms; Speech recognition; Stability analysis;
Journal_Title :
Neural Networks, IEEE Transactions on