数学
霍普夫分叉
独特性
平衡点
应用数学
常微分方程
理论(学习稳定性)
特征向量
拉普拉斯变换
分叉
分岔理论
分叉理论的生物学应用
人工神经网络
订单(交换)
数学分析
微分方程
非线性系统
计算机科学
量子力学
财务
机器学习
物理
经济
作者
R. Rakkiyappan,K. Udhayakumar,G. Velmurugan,Jinde Cao,Ahmed Alsaedi
标识
DOI:10.1186/s13662-017-1266-3
摘要
This paper considers a class of fractional-order complex-valued Hopfield neural networks (CVHNNs) with time delay for analyzing the dynamic behaviors such as local asymptotic stability and Hopf bifurcation. In the case of a neural network with hub and ring structure, the stability of the equilibrium state is investigated by analyzing the eigenvalue of the corresponding characteristic matrix for the hub and ring structured fractional-order time delay models using a Laplace transformation for the Caputo-fractional derivatives. Some sufficient conditions are established to guarantee the uniqueness of the equilibrium point. In addition, conditions for the occurrence of a Hopf bifurcation are also presented. Finally, numerical examples are given to demonstrate the effectiveness of the derived results.
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