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A high dimensional stochastic resonance system and its application in signal processing

Author

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  • Zhou, Zuanbo
  • Yu, Wenxin
  • Wang, Junnian
  • Liu, Meiting

Abstract

At present, the stochastic resonance (SR) theory based on the traditional model with periodic input signal has been extensively studied. To further investigate dynamic process and improve the universality of SR system, a high-dimensional SR model is proposed in this paper. By analyzing the dynamic characteristics, the SR phenomenon is explained from the perspective of equilibrium point which is driven by the input signal. The expression of some key parameters is derived, and the noise reduction of aperiodic image signal is studied. Experimental results show that the SR phenomenon can be induced by appropriate input signal, and the proposed high-dimensional SR system has obvious noise reduction effect on aperiodic image signals, which further widens the application of SR theory in signal processing.

Suggested Citation

  • Zhou, Zuanbo & Yu, Wenxin & Wang, Junnian & Liu, Meiting, 2022. "A high dimensional stochastic resonance system and its application in signal processing," Chaos, Solitons & Fractals, Elsevier, vol. 154(C).
    • Handle: RePEc:eee:chsofr:v:154:y:2022:i:c:s0960077921009966
    DOI: 10.1016/j.chaos.2021.111642
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    Cited by:

    1. Zhu, Jinjie & Zhao, Feng & Li, Yang & Liu, Xianbin, 2024. "Rotational stochastic resonance in multistable systems," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 634(C).
    2. Zhang, Gang & Chen, Yezi & Xu, Lianbing, 2024. "Multi-dimensional hybrid potential stochastic resonance and application of bearing fault diagnosis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 634(C).
    3. He, Lifang & Jiang, Zhiyuan & Chen, Yezi, 2024. "Unveiling the principles of stochastic resonance and complex potential functions for bearing fault diagnosis," Chaos, Solitons & Fractals, Elsevier, vol. 180(C).

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