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Weak-Periodic Stochastic Resonance in a Parallel Array of Static Nonlinearities

Author

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  • Yumei Ma
  • Fabing Duan
  • François Chapeau-Blondeau
  • Derek Abbott

Abstract

This paper studies the output-input signal-to-noise ratio (SNR) gain of an uncoupled parallel array of static, yet arbitrary, nonlinear elements for transmitting a weak periodic signal in additive white noise. In the small-signal limit, an explicit expression for the SNR gain is derived. It serves to prove that the SNR gain is always a monotonically increasing function of the array size for any given nonlinearity and noisy environment. It also determines the SNR gain maximized by the locally optimal nonlinearity as the upper bound of the SNR gain achieved by an array of static nonlinear elements. With locally optimal nonlinearity, it is demonstrated that stochastic resonance cannot occur, i.e. adding internal noise into the array never improves the SNR gain. However, in an array of suboptimal but easily implemented threshold nonlinearities, we show the feasibility of situations where stochastic resonance occurs, and also the possibility of the SNR gain exceeding unity for a wide range of input noise distributions.

Suggested Citation

  • Yumei Ma & Fabing Duan & François Chapeau-Blondeau & Derek Abbott, 2013. "Weak-Periodic Stochastic Resonance in a Parallel Array of Static Nonlinearities," PLOS ONE, Public Library of Science, vol. 8(3), pages 1-7, March.
  • Handle: RePEc:plo:pone00:0058507
    DOI: 10.1371/journal.pone.0058507
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