Paper Info
Title
Stochastic stability and bifurcation analysis on Hopfield neural networks with noise.
Abstract
A stochastic differential equation modelling a Hopfield neural network with two neurons is investigated. By analyzing the Lyapunov exponent, invariant measure and singular boundary theory, its nonlinear stochastic stability is investigated and stochastic D (P)-bifurcations are demonstrated. The stochastic stability and D (P)-bifurcation are determined from the random dynamical and phenomenological points of view. Numerical simulation results are given to support the theoretical predictions. (C) 2011 Elsevier Ltd. All rights reserved.
Year
DOI
Venue
2010
10.1016/j.eswa.2011.02.111
EXPERT SYSTEMS WITH APPLICATIONS
Keywords
DocType
Volume
Stochastic stability and bifurcation,Lyapunov exponent,Invariant measure,Hopfield neural network
Conference
38
Issue
ISSN
Citations 
8
0957-4174
3
PageRank 
References 
Authors
0.56
11
3
Name
Order
Citations
PageRank
Zaitang Huang142.32
Qigui Yang216926.54
Junfei Cao341.64