Global stability and bifurcation in delayed BAM neural networks with an arbitrary number of neurons

[+] Author and Article Information
Elham Javidmanesh

Department of Applied Mathematics, Ferdowsi University of Mashhad, Mashhad, Iran

1Corresponding author.

ASME doi:10.1115/1.4036229 History: Received October 06, 2015; Revised February 11, 2017


In this paper, delayed BAM neural networks, which consist of one neuron in the X-layer and other neurons in the Y-layer, will be studied. Hopf bifurcation analysis of these systems will be discussed by proposing a general method. In fact, a general n-neuron BAM neural network model is considered and the associated characteristic equation is studied by classification according to n. Here, n can be chosen arbitrarily. Moreover, we find an appropriate Lyapunov function that under a hypothesis, results in global stability. Numerical examples are also presented.

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