Abstract: Aiming at the detection problem of the multi-frequency signal under noise background, a novel method based on empirical mode decomposition(EMD) after de-noising by adaptive re-scaling frequency-shifted band-pass stochastic resonance is proposed. In this method, different frequency bands of the signal are processed by re-scaling sub-sampling compression to make each frequency band meet the conditions of stochastic resonance. Further parameters are adaptively optimized according to noise intensity and the weak signal frequency components are enhanced through stochastic resonance system. Before the enhanced components of the signal are synthesized, they are processed through band-pass filter only leaving the enhanced sections of the signal, to achieve the enhancement signal. The processed signal is decomposed by EMD into intrinsic mode functions to achieve detection of multi-frequency weak signals. The simulation results show that the proposed method, can enhance the signal amplitude, reduce the false component and improve the accuracy of the EMD algorithm, effectively detect multi-frequency weak signal submerged by noise.

Key words: Adaptive parameter optimization, Empirical mode decomposition, Multi-frequency weak signal detection, Stochastic resonance