Research On Aperiodic Signal Detecting Based On Piecewise-Hybrid Stochastic Resonance Model

Since stochastic resonance was proposed in the1980s, it has developed near30years, made many progresses both in theory and experimental study, and applied in physics, chemistry, the biology, the correspondence, the information theory, electronics, optics, the superconductivity, the neural network and so on, especially its application in the weak signal detection has arouse the numerous scholar’s interests. This article points out the saturated phenomenon which exists in the classical bistable system, so we proposed a new piecewise hybrid model to avoid the saturation, and has done a lot of research on its application in weak signal detection under the adiabatic approximation.Firstly, this paper describes the motion of Brownian particle by motion equation at the macro level and the random force in the random level to elaborate a Langevin equation; introducing the adiabatic approximation theory and explain reason which stochastic resonance produces. And we also studied the signal output SNR for the output signals of the Bi-Stable Langevin model when changing the noise intensity and the system parameters, and give the definition of the output bit error rate (BER) for nonlinear system, while the input signals is aperiodic signal such as baseband binary pulse amplitude modulation (PAM) signal. All these are to provide a theoretical basis for the follow-up study.Second, this paper theoretically analyzes the saturation exists in the classical bistable system, and validate it through numerical simulation; Propose a new piecewise hybrid stochastic resonance model, and analyze the reasons for its saturation does not exist.Then, the piecewise hybrid model was used for non-periodic signal detection research, and for the binary aperiodic signal, M and as the input signals for the piecewise hybrid model, the probability characteristics of the output signal and the output of sub-linear model signal to noise ratio were studied. And the detection on binary aperiodic signals based on the piecewise linear model, we found that through an appropriate adjustment to the noise intensity and system parameters, there is an optimum value achieved for non-periodic signal detection. And then analyzes the effect of the signal rate on the piecewise hybrid stochastic resonance model.And then do some research on image processing based on the piecewise hybrid stochastic resonance model, Analyze the effect of the system parameters and noise to the image quality.Finally, based on the numerical analysis, we implement the circuit model of the piecewise hybrid model, completing the design and debug the circuit of the model. Then do some preliminary experiment, finally do some summarize for the experiment.