Title: Global exponential stability for stochastic Cohen-Grossberg neural networks with multiple time-varying delays

Authors: N. Mala; A.R. Sudamani Ramaswamy

Addresses: Department of Mathematics, Kovai Kalaimagal College of Arts and Science, Coimbatore-641 109, Tamil Nadu, India ' Department of Mathematics, Avinashilingam Deemed University for Women, Coimbatore-641 043, Tamil Nadu, India

Abstract: In this paper, together with some Lyapunov functionals and effective mathematical techniques, sufficient conditions are derived to guarantee a class of stochastic Cohen-Grossberg neural networks with multiple time-varying delays to be globally exponential stability by using linear matrix inequality (LMI) approach. Finally, a numerical example is provided to demonstrate the effectiveness of the proposed method by using MATLAB LMI toolbox.

Keywords: global exponential stability; linear matrix inequality; LMI; Lyapunov functional; multiple time-varying delays; stochastic Cohen-Grossberg neural networks.

DOI: 10.1504/IJMMNO.2013.059204

International Journal of Mathematical Modelling and Numerical Optimisation, 2013 Vol.4 No.4, pp.374 - 386

Available online: 07 Feb 2014 *

Full-text access for editors Access for subscribers Purchase this article Comment on this article