Global exponential stability of recurrent neural networks with time-varying delay

Authors:
Yi Shen;Meiqin Liu;Xiaodong Xu
Affiliations:
Department of Control Science and Engineering, Huazhong University of Science and Technology, Wuhan, Hubei, China;College of Electrical Engineering, Zhejiang University, Hangzhou, China;College of Public Administration, Huazhong University of Science and Technology, Wuhan, Hubei, China
Venue:
ISNN'06 Proceedings of the Third international conference on Advances in Neural Networks - Volume Part I
Year:
2006

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Abstract

A new theoretical result on the global exponential stability of recurrent neural networks with time-varying delay is presented. It should be noted that the activation functions of recurrent neural network do not require to be bounded. The presented criterion, which has the attractive feature of possessing the structure of linear matrix inequality, is a generalization and improvement over some previous criteria.