Global Stability and Chaos-Control in Delayed N-Cellular Neural Network Model

Conference paper
First Online:
Part of the Springer Proceedings in Mathematics & Statistics book series (PROMS, volume 146)

Abstract

In this paper stability, bifurcation, and chaotic behavior of a cellular neural network (CNN) model which is a regular array of n (\(\ge \)3) cells with continuous activation function are presented. In the delayed cellular neural network model (DCNN) criteria for the global asymptotic stability of the equilibrium point is presented by constructing suitable Lyapunov functional. Numerical simulations are given to verify the analytical results. The role of delay in chaos control of the CNNs has been shown numerically.

Keywords

Time delay Global asymptotic stability Chaos control Cellular neural network 
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Copyright information

© Springer India 2015

Authors and Affiliations

  1. 1.Department of MathematicsIIEST, ShibpurHowrahIndia

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