Stability and Hopf bifurcation of three-triangle neural networks with delays

被引：30

作者：

Cheng, Zunshui ^{[1
]}

Xie, Konghe ^{[1
]}

Wang, Tianshun ^{[1
]}

Cao, Jinde ^{[2
]}

机构：

[1] Qingdao Univ Sci & Technol, Sch Math & Phys, Qingdao 266061, Peoples R China

[2] Southeast Univ, Sch Math, Nanjing 210096, Jiangsu, Peoples R China

来源：

NEUROCOMPUTING | 2018年 / 322卷

基金：

中国国家自然科学基金;

关键词：

Neural networks; Delays; Hopf Bifurcation; DISTRIBUTED DELAYS; TIME-DELAY; COMPLEX NETWORKS; 2-NEURON SYSTEM; DISCRETE; DYNAMICS;

D O I：

10.1016/j.neucom.2018.09.063

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this paper, a neural networks model with seven neurons and time delay is considered. The model can be described as three triangles sharing one node. The local asymptotical stability of the trivial equilibrium point is studied by analyzing the corresponding characteristic equation. By using the delay as bifurcation parameter, the critical value of bifurcation is given, and then the stability and Hopf bifurcation of the model are discussed. In addition, the stability and bifurcation direction of the bifurcation periodic solution are discussed by using the central manifold theorem and the norm form. The validity of the above theoretical results is verified by numerical simulation. (C) 2018 Elsevier B. V. All rights reserved

引用

页码：206 / 215

页数：10

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