Global stability and Hopf bifurcation of delayed fractional-order complex-valued BAM neural network with an arbitrary number of neurons

被引:1
|
作者
Javidmanesh, Elham [1 ]
Bahabadi, Alireza Zamani [2 ]
机构
[1] Ferdowsi Univ Mashhad, Dept Appl Math, Mashhad, Iran
[2] Ferdowsi Univ Mashhad, Dept Pure Math, Mashhad, Iran
来源
JOURNAL OF MATHEMATICAL MODELING | 2023年 / 11卷 / 01期
关键词
neural network; fractional ordinary differential equations; Hopf bifurcation; time delay; Lyapunov function; global stability;
D O I
10.22124/JMM.2022.22299.1972
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
In this paper, a general class of fractional-order complex-valued bidirectional associative memory neural network with time delay is considered. This neural network model contains an arbitrary number of neurons, i.e. one neuron in the X-layer and other neurons in the Y-layer. Hopf bifurcation analysis of this system will be discussed. Here, the number of neurons, i.e., n can be chosen arbitrarily. We study Hopf bifurcation by taking the time delay as the bifurcation parameter. The critical value of the time delay for the occurrence of Hopf bifurcation is determined. Moreover, we find two kinds of appropriate Lyapunov functions that under some sufficient conditions, global stability of the system is obtained. Finally, numerical examples are also presented.
引用
收藏
页码:19 / 34
页数:16
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