Stability and Hopf bifurcation of a delayed Cohen-Grossberg neural network with diffusion

被引:4
作者
Tian, Xiaohong [1 ]
Xu, Rui [1 ]
机构
[1] Shijiazhuang Mech Engn Coll, Inst Appl Math, Shijiazhuang 050003, Peoples R China
基金
中国国家自然科学基金;
关键词
Cohen-Grossberg neural network; time delay; diffusion; stability; Hopf bifurcation; TIME-VARYING DELAYS; EXPONENTIAL STABILITY; ROBUST STABILITY; BOUNDEDNESS; BEHAVIOR;
D O I
10.1002/mma.3995
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
In this paper, a delayed Cohen-Grossberg neural network with diffusion under homogeneous Neumann boundary conditions is investigated. By analyzing the corresponding characteristic equation, the local stability of the trivial uniform steady state and the existence of Hopf bifurcation at the trivial steady state are established, respectively. By using the normal form theory and the center manifold reduction of partial function differential equations, formulae are derived to determine the direction of bifurcations and the stability of bifurcating periodic solutions. Numerical simulations are carried out to illustrate the main results. Copyright (C) 2016 John Wiley & Sons, Ltd.
引用
收藏
页码:293 / 305
页数:13
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