Research On A Signal Detecting Based On Piecewise-linear Stochastic Resonance Model

Since the eighties of last century, Stochastic Resonance has been proposed to be used for weak signal detection. The original signal and noise could generate the synergistic effect to ultimately achieve the goals that reducing noise and detecting the signals in this non-linear system. As the research object, the new piece-wise linear Stochastic Resonance model which is proposed by us, we studied about detection of weak signal that under the noise base on Stochastic Resonance theory.This paper first introduced the classic Bi-stable Stochastic Resonance model, and then studied on the potential function of Bi-stable model to explain the causes of stochastic resonance. It introduced the classical theory of stochastic resonance and analyzed the procreant mechanism of theStochastic Resonance, the relationship among noise, signal and Bi-stable System. We also described the theory of Fourier transform which prepared to be used in Paper. Secondly, for our proposed piecewise-linear stochastic resonance model, we described the potential function and parameters corresponded to the model. Then we compared the piece-wise linear model and Bi-stable model by numerical methods. We discussed the Stochastic Resonance behavior of the two models when take those two models under the condition of noise or non-noise for deep understanding about the piece-wise linear Stochastic Resonance model. Studies have shown that the piece-wise linear system can produce Stochastic Resonance behavior with the appropriate parameters and driven period signal. The more importantly, within strong noise, piece-wise linear model is better than the classic Bi-stable model on signal extraction. After that, paper focused on the piece-wise linear circuit model of Stochastic Resonance. We started with the basic unit of the circuit, introduced the basic unit of linear and nonlinear circuit. The specific design and implementation of programs is given by decomposing the piece-wise linear model into a number of small modules. The hardware circuit is debugged and achieved.Finally, base on the above hardware circuit, the sine wave, square wave, triangular-wave and other typical period signals is choose t for the weak signal detection in experimental research. In the absence of noise and noise conditions, the selection of parameters, the noise strength, the changes of signal to noise ratio are all carried out in a certain amount of experimental study. The experiment results showed that the circuit system can effectively detect weak sine signal and a variety of other type of signal, and laid the foundation for engineering applications for the future.This research is subsidized by the project"Research on nonlinear filter theory and technology based on Stochastic Resonance theory", which is supported by National Natural Science Funding.Innovation points: (1) Designed and implemented hardware circuit base on piece-wise linear Stochastic Resonance model; (2) Had the signal detection experimental research on the hardware circuit, laid the foundation for engineering applications for the future.