Global exponential stability of the periodic solution of delayed Cohen-Grossberg neural networks with discontinuous activations

Authors:
Xiaofeng Chen;Qiankun Song
Affiliations:
Department of Mathematics, Chongqing Jiaotong University, Chongqing 400074, China;Department of Mathematics, Chongqing Jiaotong University, Chongqing 400074, China
Venue:
Neurocomputing
Year:
2010

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Abstract

In the paper, the problem on the stability of periodic solutions is investigated for delayed Cohen-Grossberg neural networks with discontinuous activations. For the neural networks under study, the traditional assumptions on the Lipschitz continuity and some sort of linear growth for the activation functions are not required. By employing the theory of differential equations with discontinuous right-hand side, theory of fixed point and Lyapunov approach, several sufficient conditions for checking the existence, uniqueness and global exponential stability of periodic solution for the considered neural networks are given. Three numerical examples with simulations are given to show the effectiveness and less conservatism of the proposed criteria.