Stochastic resonance in FHN neural system driven by non-Gaussian noise

Jing Jing Zhang*, Yan Fei Jin

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

15 Citations (Scopus)

Abstract

Stochastic resonance (SR) is studied in the FitzHugh-Nagumo (FHN) neural system subject to multiplicative non-Gaussian noise, additive Gaussian white noise and a periodic signal. Using the path integral approach and the two-state theory, the expression of the signal-to-noise ratio (SNR) is derived. The simulation results show that conventional SR and double SR occur in the FHN neural model under different values of system parameters. The effects of the additive and multiplicative noise intensities on SNR are different. Moreover, the addition of non-Gaussian noise is conductive to the enhancement of the response to the output signal of the FHN neural system.

Original languageEnglish
Article number130502
JournalWuli Xuebao/Acta Physica Sinica
Volume61
Issue number13
Publication statusPublished - 5 Jul 2012

Keywords

  • FHN neural system
  • Non-Gaussian noise
  • Stochastic resonance

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