Research On Weak Signal Extraction Based On Parameter Adjustment Stochastic Resonance

As a nonlinear signal processing,stochastic resonance can be applied to extract signal based on its strong sensitivity for weak signal.This paper begin with the theoretical research on bistable stochastic resonance,and gradually discuss the theory and system adjustment of stochastic resonance,and the adaptability of different waveforms.Finally,a new Stochastic Resonance System can be used in practical engineering based on Genetic Optimization Parameter Adjustment.The bistable system is determined by Lonerge's equation under one-dimensional nonlinear conditions.It has the obvious anti-intuitionistic characteristic that the output is slowly getting better and then gradually getting worse.The form of the bistable potential function directly affects the output effect.By studying the potential function,the meaning of the output distribution is further clarified.Compared with the Notch filter,classical single-frequency signal processing method,stochastic resonance shows excellent extracting ability.This paper has given the method of system adjustment under large parameters and the realization of cascaded stochastic resonance system.By the analysis of the noise tuning with signal conditioning method,this paper presents a parametric adjustment stochastic resonance system with more regulation capability.The influence of system parameters on steady-state signal-noise ratio and response speed was quantified by theoretical analysis and simulation comparison.In order to realize the self-adjusting of system parameters and blind searching,this paper propose a parameter-adjusting stochastic resonance algorithm based on genetic optimization to improve the adjusting speed in practical application.For different forms of signals,this paper uses the up sampling to extract the LFM signals.Using monostable system,the impulse signal was extracted.Using the stochastic resonance recovery system,this paper expands the application range of stochastic resonance.Finally,this paper shows the process of system implem.