Novel criteria on global exponential stability of fuzzy Cohen-Grossberg neural networks with time-varying delay

Authors:
Yongsu Kim;Huaguang Zhang;Xin Zhang;Lili Cui
Affiliations:
Information Science and Engineering, Northeastern University, Shenyang, China;Information Science and Engineering, Northeastern University, Shenyang, China;Information Science and Engineering, Northeastern University, Shenyang, China;Information Science and Engineering, Northeastern University, Shenyang, China
Venue:
CCDC'09 Proceedings of the 21st annual international conference on Chinese control and decision conference
Year:
2009

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Abstract

Global exponential stability problem of the fuzzy Cohen-Grossberg neural networks (FCGNNs) with time-varying delay is considered in this paper. By using the Lyapunov-Krasovskii method, the novel sufficient conditions are obtained to guarantee the global exponential stability of the considered system. These conditions are expressed in the terms of linear matrix inequalities (LMIs), and can be checked by resorting to the Matlab LMI Toolbox. Finally, a numerical example is given to show the effectiveness of the obtained results.