Bifurcation Analysis in a Three-Neuron Artificial Neural Network Model with Distributed Delays

被引：0
|
作者：
Changjin Xu
Qiming Zhang
Yusen Wu
机构：
[1] Guizhou University of Finance and Economics,Guizhou Key Laboratory of Economics System Simulation
[2] Hunan University of Technology,College of Science
[3] Henan University of Science and Technology,School of Mathematics and Statistics
来源：
Neural Processing Letters | 2016年 / 44卷
关键词：
Artificial neural network; Stability; Hopf bifurcation; Distributed delay; Periodic solution; 34K20; 34C25;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
In this paper, a three-neuron artificial neural network model with distributed delays is considered. Its dynamics is investigated in term of the linear stability analysis and Hopf bifurcation analysis. By regarding the sum of two delays as a bifurcation parameter and analyzing the associated characteristic equation, we find that Hopf bifurcation occurs when the bifurcation parameter passes through some certain values. Some explicit formulae for determining the stability and the direction of the Hopf bifurcation periodic solutions are derived by using the normal form method and center manifold theory. Finally, computer simulations are given to support the theoretical predictions.
引用
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页码：343 / 373
页数：30
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