A feature extraction approach of weak signals based on Stochastic resonance and blind source separationL

An effective approach is presented to eliminate heavy noise in weak signal by SR (stochastic resonance) and BSS (blind source seperation), through which the noise caused by the uncorrelated factors can be removed successfully. This method which is demonstrated by numerical examples, is used for useful weak mixing signal analysis and is powerful in weaksignal feature extraction especially for useful weak signal buried in noise. The main conceptual innovations in this method are the associated introduction of 'stochastic resonance' and 'source seperation' based on the local properties of the mixed signals, which makes the feature frequency meaningful. This method serves to illustrate the roles played by nonlinear effects in the mixing weak signals with heavy noise. At the same time, the method can also be expanded and applied in other fields.