Features extraction based on singular value decomposition and stochastic resonance

In order to detect the weak characteristic signal submerged in heavy noise with extremely low signal-to-noise ratio, a method based on singular value decomposition (SVD) and stochastic resonance is proposed. The sampling signal is first preprocessed and reconstructed by means of SVD, and then we search for a component signal. In the component signal, the components of the characteristic signal match noise strength. Then the component signal is processed with the non-linear bistable system to obtain stochastic resonance response, thus the goal of detecting the weak characteristic signal submerged in a heavy background noise is realized.