Global exponential stability of reaction-diffusion hopfield neural networks with distributed delays

Authors:
Zhihong Tang;Yiping Luo;Feiqi Deng
Affiliations:
College of Automation Science and Engineering, South China University of Technology, Guangdong, Guangzhou, China;College of Automation Science and Engineering, South China University of Technology, Guangdong, Guangzhou, China;College of Automation Science and Engineering, South China University of Technology, Guangdong, Guangzhou, China
Venue:
ISNN'05 Proceedings of the Second international conference on Advances in Neural Networks - Volume Part I
Year:
2005

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Abstract

The global exponential stability of reaction-diffusion Hopfield neural networks with distributed delays is studied. Without assuming the boundedness, monotonicity and differentiability of the activation functions, the sufficient conditions were obtained by utilizing Dini's derivative, F-function and extended Hanaly's inequality. These conditions are easy to check and apply in practice and can be regarded as an extension of existing results.