Delay-dependent exponential stability analysis for discrete-time switched neural networks with time-varying delay

Authors:
Zheng-Guang Wu;Peng Shi;Hongye Su;Jian Chu
Affiliations:
National Laboratory of Industrial Control Technology, Institute of Cyber-Systems and Control, Zhejiang University, Yuquan Campus, Hangzhou Zhejiang 310027, PR China;Department of Computing and Mathematical Sciences, University of Glamorgan, Pontypridd CF37 1DL, UK and School of Engineering and Science, Victoria University, Melbourne, 8001 Vic, Australia;National Laboratory of Industrial Control Technology, Institute of Cyber-Systems and Control, Zhejiang University, Yuquan Campus, Hangzhou Zhejiang 310027, PR China;National Laboratory of Industrial Control Technology, Institute of Cyber-Systems and Control, Zhejiang University, Yuquan Campus, Hangzhou Zhejiang 310027, PR China
Venue:
Neurocomputing
Year:
2011

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Abstract

In this paper, we focus on the stability problem for discrete-time switched neural networks with time-varying delay resorting to the average dwell time method. In terms of linear matrix inequality approach, a delay-dependent sufficient condition of exponential stability is developed for a kind of switching signal with average dwell time. A numerical example is given to show the validness of the established result.