Open AccessThe steady state probability distribution and mean first passage time of FHN neural system driven by non-Gaussian noise
Author(s) -
Zhao Yan,
Wei Xu,
Zou Shao-Cun
Publication year - 2009
Publication title -
wuli xuebao
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.199
H-Index - 47
ISSN - 1000-3290
DOI - 10.7498/aps.58.1396
Subject(s) - gaussian noise , noise (video) , multiplicative noise , gaussian , statistical physics , physics , probability distribution , first hitting time model , intensity (physics) , multiplicative function , stationary distribution , transmission (telecommunications) , mathematics , computer science , mathematical analysis , statistics , algorithm , optics , quantum mechanics , artificial intelligence , telecommunications , signal transfer function , analog signal , image (mathematics) , markov chain
We investigated the FitzHugh-Nagumo neural system driven by non-Gaussian noise. The expressions of the stationary probability distribution and the mean first-passage time are obtained through the path-integral approach and the unified colored noise approximation. The results show that the intensity of additive noise can induce phase transitionwhile the intensity of multiplicative noisethe derivation parameter and the correlation time cannot. The non-Gaussian noise shortens transformation time between resting state and excited state and is beneficial to transmission of information in neural system.