Characterization of stochastic resonance in a bistable system with Poisson white noise using statistical complexity measures

• Statistical complexity measures, as new methods, are employed to quantify the stochastic resonance of bistable system under Poisson white noise.
• The effects of Poisson white noise and different periodic signals on stochastic resonance are investigated in detail.
• The results demonstrate that statistical complexity measures are effective methods for detecting stochastic resonance in the presence of Poisson white noise.
• The influence of rectangular signal on stochastic resonance is more significant than other two periodic signals.

This paper mainly investigates the phenomenon of stochastic resonance (SR) in a bistable system subjected to Poisson white noise. Statistical complexity measures, as new tools, are first employed to quantify SR phenomenon of given system with Poisson white noise. To begin with, the effect of Poisson white noise on SR phenomenon is studied. The results demonstrate that the curves of statistical complexity measures as a function of Poisson white noise intensity exhibit non-monotonous structure, revealing the existence of SR phenomenon. Besides, it should be noted that small mean arrival rate of Poisson white noise can promote the occurrence of SR. In order to verify the effectiveness of statistical complexity measures, signal-to-noise ratio (SNR) is also calculated. A good agreement among these results obtained by statistical complexity measures and SNR is achieved, which reveals that statistical complexity measures are suitable tools for characterizing SR phenomenon in the presence of Poisson white noise. Then, the effects of amplitude and frequency of different periodic signals, including cosine, rectangular and triangular signal, on SR behavior are investigated, respectively. One can observe that, in the case of same amplitude or frequency of signal, the influence of rectangular signal on SR phenomenon is the most significant among these three signals.