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Optimal weighted suprathreshold stochastic resonance with multigroup saturating sensors

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  • Xu, Liyan
  • Duan, Fabing
  • Abbott, Derek
  • McDonnell, Mark D.

Abstract

Suprathreshold stochastic resonance (SSR) describes a noise-enhanced effect that occurs, not in a single element, but rather in an array of nonlinear elements when the signal is no longer subthreshold. Within the context of SSR, we investigate the optimization problem of signal recovery through an array of saturating sensors where the response of each element can be optimally weighted prior to summation, with a performance measure of mean square error (MSE). We consider groups of sensors. Individual sensors within each group have identical parameters, but each group has distinct parameters. We find that optimally weighting the sensor responses provides a lower MSE in comparison with the unweighted case for weak and moderate noise intensities. Moreover, as the slope parameter of the nonlinear sensors increases, the MSE superiority of the optimally weighted array shows a peak, and then tends to a fixed value. These results indicate that SSR with optimal weights, as a general mechanism of enhancement by noise, is of potential interest to signal recovery.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:phsmap:v:457:y:2016:i:c:p:348-355
    DOI: 10.1016/j.physa.2016.03.064
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    References listed on IDEAS

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    1. Sergey M. Bezrukov & Igor Vodyanoy, 1997. "Erratum: Stochastic resonance in non-dynamical systems without response thresholds," Nature, Nature, vol. 386(6626), pages 738-738, April.
    2. Duan, Fabing & Chapeau-Blondeau, François & Abbott, Derek, 2009. "Input–output gain of collective response in an uncoupled parallel array of saturating dynamical subsystems," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(8), pages 1345-1351.
    3. Zeng, Lingzao & Xu, Bohou, 2010. "Effects of asymmetric Lévy noise in parameter-induced aperiodic stochastic resonance," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(22), pages 5128-5136.
    4. Sergey M. Bezrukov & Igor Vodyanoy, 1997. "Stochastic resonance in non-dynamical systems without response thresholds," Nature, Nature, vol. 385(6614), pages 319-321, January.
    5. Zhou, Bingchang & McDonnell, Mark D., 2015. "Optimising threshold levels for information transmission in binary threshold networks: Independent multiplicative noise on each threshold," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 419(C), pages 659-667.
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    Cited by:

    1. Xie, Tianting & Ji, Yuandong & Yang, Zhongshan & Duan, Fabing & Abbott, Derek, 2023. "Optimal added noise for minimizing distortion in quantizer-array linear estimation," Chaos, Solitons & Fractals, Elsevier, vol. 166(C).

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