Local and global Hopf bifurcation analysis on simplified bidirectional associative memory neural networks with multiple delays

被引:44
|
作者
Xu, Changjin [1 ]
机构
[1] Guizhou Univ Finance & Econ, Guizhou Key Lab Econ Syst Simulat, Guiyang 550004, Guizhou, Peoples R China
基金
中国国家自然科学基金;
关键词
Neural networks; Stability; Hopf bifurcation; Delay; Periodic solution; FUNCTIONAL-DIFFERENTIAL EQUATIONS; DISTRIBUTED DELAYS; TIME DELAYS; PERIODIC-SOLUTIONS; 2-NEURON SYSTEM; STABILITY; MODEL; EXISTENCE; DISCRETE; DYNAMICS;
D O I
10.1016/j.matcom.2018.02.002
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
In this paper, a class of simplified bidirectional associative memory (BAM) neural networks with multiple delays are considered. By analyzing the associated characteristic transcendental equation, their linear stability is investigated and Hopf bifurcation is demonstrated. By applying Nyquist criterion, the length of delay which preserves the stability of the zero equilibrium is estimated. Some explicit results are derived for stability and direction of the bifurcating periodic orbit by using the normal form theory and center manifold arguments. Global existence of periodic orbits is also established by using a global Hopf bifurcation theorem for functional differential equations (FDE) and a Bendixson's criterion for high-dimensional ordinary differential equations (ODE) due to Li and Muldowney. Finally, numerical simulations supporting the theoretical analysis are carried out. (C) 2018 International Association for Mathematics and Computers in Simulation (IMACS). Published by Elsevier B.V. All rights reserved.
引用
收藏
页码:69 / 90
页数:22
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