Table of Contents
Advances in Artificial Neural Systems
Volume 2014, Article ID 369230, 8 pages
http://dx.doi.org/10.1155/2014/369230
Research Article

Global Stability, Bifurcation, and Chaos Control in a Delayed Neural Network Model

Department of Mathematics, Indian Institute of Engineering Science and Technology, Shibpur, Howrah 711103, India

Received 29 May 2014; Accepted 15 September 2014; Published 8 October 2014

Academic Editor: Matt Aitkenhead

Copyright © 2014 Amitava Kundu and Pritha Das. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Conditions for the global asymptotic stability of delayed artificial neural network model of n (≥3) neurons have been derived. For bifurcation analysis with respect to delay we have considered the model with three neurons and used suitable transformation on multiple time delays to reduce it to a system with single delay. Bifurcation analysis is discussed with respect to single delay. Numerical simulations are presented to verify the analytical results. Using numerical simulation, the role of delay and neuronal gain parameter in changing the dynamics of the neural network model has been discussed.