A study on the parameters of bistable stochastic resonance systems and adaptive stochastic resonance

Abstract

Noise can improve the signal-to-noise ratio of many nonlinear dynamical systems. This ''stochastic resonance" (SR) effect occurs in a wide range of physical and biological systems, and also occurs in engineering systems in signal processing, communications, and control. Most SR studies assume the signal and noise properties are known. To overcome this limitation, we give a type of adaptive stochastic resonance. This paper present a novel approach for investigating the relationships among the parameters of a bistable SR system, based on the characteristics of digital simulations. Using this approach, we can obtain the system's responses with varying parameters and these responses are consistent with experimental results. As a direct application, a system can be moved into the SR condition by conveniently changing its structural parameters, even when it is forced by an unknown periodic signal embedded in a white Gaussian noise with unknown statistical properties.