Novel stability criteria of Cohen–Grossberg neural networks with time-varying delays

Authors:
Cheng-De Zheng;Qi-He Shan;Zhanshan Wang
Affiliations:
School of Science, Dalian Jiaotong University, Dalian 116028, People's Republic of China;School of Science, Dalian Jiaotong University, Dalian 116028, People's Republic of China;School of Information Science and Engineering, Northeastern University, Shenyang 110004, People's Republic of China
Venue:
International Journal of Circuit Theory and Applications
Year:
2012

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Abstract

In this paper, a class of Cohen–Grossberg neural networks with time-varying delays is investigated. Based on several new Lyapunov–Krasovskii functionals, by employing the homeomorphism mapping principle, the Halanay inequality, a nonlinear measure approach and linear matrix inequality techniques, several delay-independent sufficient criteria are obtained for the existence, uniqueness and globally exponential stability of considered neural networks. Without assuming the boundedness and monotonicity of activation functions, the obtained conditions generalize some previous results in the literature. Two examples are also given to show the less conservativeness of the obtained conditions. Copyright © 2010 John Wiley & Sons, Ltd.