A Blind Source Separation Algorithm Based on Whitening and Non-linear Decorrelation

Blind source separation (BSS) methods become more attractive targets in neural network and signal processing literature recently. And independent component analysis (ICA) methods are one kind of widely used and important solutions to blind source separation problems. Whitening is a very useful preparation step for blind separation of source and meanwhile non-linear decorrelation acts as a basic estimation theory upon ICA methods. Then an on-line real-time blind source separation algorithm based on the whitening and non-linear decorrelation is proposed in this paper. Performance of the proposed method is simulated and analyzed and then the results show that our proposed algorithm has better convergence speed and steady-state error than the normalized EASI, nature gradient and whitening-only methods.