Novel LMI Criteria for Stability of Neural Networks with Distributed Delays

Authors:
Qiankun Song;Jianting Zhou
Affiliations:
Department of Mathematics, Chongqing Jiaotong University, Chongqing 400074, China;College of Civil Engineering and Architecture, Chongqing Jiaotong University, Chongqing 400074, China
Venue:
ISNN '07 Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks
Year:
2007

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Abstract

In this paper, the global asymptotic and exponential stability are investigated for a class of neural networks with distributed time-varying delays. By using appropriate Lyapunov-Krasovskii functional and linear matrix inequality (LMI) technique, two delay-dependent sufficient conditions in LMIs form are obtained to guarantee the global asymptotic and exponential stability of the addressed neural networks. The proposed stability criteria do not require the monotonicity of the activation functions and the differentiability of the distributed time-varying delays, which means that the results generalize and further improve those in the earlier publications. An example is given to show the effectiveness of the obtained condition.