物理学报2012，Vol.61Issue(13)：36-42,7.
非高斯噪声激励下FitzHugh-Nagumo神经元系统的随机共振
Stochastic resonance in FHN neural system driven by non-Gaussian noise
摘要
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-Ganssian noise is conductive to the enhancement of the response to the output signal of the FHN neural system.关键词
非高斯噪声/FHN神经元系统/随机共振Key words
non-Gaussian noise/FHN neural system/stochastic resonance分类
数理科学引用本文复制引用
张静静,靳艳飞..非高斯噪声激励下FitzHugh-Nagumo神经元系统的随机共振[J].物理学报,2012,61(13):36-42,7.基金项目
国家自然科学基金 （）
北京理工大学优秀青年教师资助计划持续支持项目（批准号：2010YS0101）资助的课题 （）
