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Effects of signal spectrum varying on signal processing by parameter-induced stochastic resonance

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  • Li, Jianlong
  • Xu, Bohou

Abstract

The effects of signal spectrum varying on signal processing by the method of parameter-induced stochastic resonance (PSR) are investigated. For a binary signal with a smooth power spectral density (PSD), when the PSD curve becomes sharper and narrower, the performance of the nonlinear system via PSR is better. For a multi-frequency signal formed by sine waves with different frequencies, the larger the signal spectral density is, the lower the ability of the PSR system processing signal is. And the signal-to-noise ratio (SNR) gain of the PSR system is increased with the increasing height of the spectral line. Moreover, with the method of PSR, the stochastic signal (the combination of sine waves and noise) improvement is obvious. The results obtained via this method are superior to those with a linear filter.

Suggested Citation

  • Li, Jianlong & Xu, Bohou, 2006. "Effects of signal spectrum varying on signal processing by parameter-induced stochastic resonance," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 361(1), pages 11-23.
    • Handle: RePEc:eee:phsmap:v:361:y:2006:i:1:p:11-23
    DOI: 10.1016/j.physa.2005.07.015
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    Cited by:

    1. Duan, Fabing & Chapeau-Blondeau, François & Abbott, Derek, 2011. "Neural signal transduction aided by noise in multisynaptic excitatory and inhibitory pathways with saturation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(16), pages 2855-2862.

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