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Stochastic resonance in non-dynamical systems without response thresholds

Author

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  • Sergey M. Bezrukov

    (National Institutes of Healthy Bethesda
    St Petersburg Nuclear Physics Institute)

  • Igor Vodyanoy

    (National Institutes of Healthy Bethesda
    Office of Naval Research, Europe
    University College London)

Abstract

The addition of noise to a system can sometimes improve its ability to transfer information reliably. This phenomenon—known as stochastic resonance—was originally proposed to account for periodicity in the Earth's ice ages1, but has now been shown to occur in many systems in physics and biology2–4. Recent experimental and theoretical work has shown that the simplest system exhibiting 'stochastic resonance' consists of nothing more than signal and noise with a threshold-triggered device (when the signal plus noise exceeds the threshold, the system responds momentarily, then relaxes to equilibrium to await the next triggering event)4–6. Here we introduce a class of non-dynamical and threshold-free systems that also exhibit stochastic resonance. We present and analyse a general mathematical model for such systems, in which a sequence of pulses is generated randomly with a probability (per unit time) that depends exponentially on an input. When this input is a sine-wave masked by additive noise, we observe an increase in the output signal-to-noise ratio as the level of noise increases. This result shows that stochastic resonance can occur in a broad class of thermally driven physico-chemical systems, such as semiconductor p–n junctions, mesoscopic electronic devices and voltage-dependent ion channels7, in which reaction rates are controlled by activation barriers.

Suggested Citation

  • Sergey M. Bezrukov & Igor Vodyanoy, 1997. "Stochastic resonance in non-dynamical systems without response thresholds," Nature, Nature, vol. 385(6614), pages 319-321, January.
  • Handle: RePEc:nat:nature:v:385:y:1997:i:6614:d:10.1038_385319a0
    DOI: 10.1038/385319a0
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    Cited by:

    1. A. Christian Silva & Ju-Yi J. Yen, 2008. "Stochastic resonance and the trade arrival rate of stocks," Papers 0807.0925, arXiv.org.
    2. Ivan Skhem Sawkmie & Mangal C. Mahato, 2021. "Stochastic resonance and free oscillation in a sinusoidal potentials driven by a square-wave periodic force," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 94(2), pages 1-10, February.
    3. Zhang, Gang & Shu, Yichen & Zhang, Tianqi, 2022. "The study on dynamical behavior of FitzHugh–Nagumo neural model under the co-excitation of non-Gaussian and colored noise," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 587(C).
    4. Xu, Liyan & Duan, Fabing & Abbott, Derek & McDonnell, Mark D., 2016. "Optimal weighted suprathreshold stochastic resonance with multigroup saturating sensors," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 457(C), pages 348-355.
    5. Liu, Shujun & Yang, Ting & Zhang, Xinzheng, 2015. "Effects of stochastic resonance for linear–quadratic detector," Chaos, Solitons & Fractals, Elsevier, vol. 77(C), pages 319-331.
    6. A. Christian Silva & Ju-Yi Yen, 2010. "Stochastic resonance and the trade arrival rate of stocks," Quantitative Finance, Taylor & Francis Journals, vol. 10(5), pages 461-466.

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