Global exponential stability analysis in cellular neural networks with time-varying coefficients and delays

Authors:
Qiang Zhang;Dongsheng Zhou;Xiaopeng Wei;Jin Xu
Affiliations:
University Key Lab of Information Science & Engineering, Dalian University, Dalian, China;School of Mechanical Engineering, Dalian University of Technology, Dalian, China;University Key Lab of Information Science & Engineering, Dalian University, Dalian, China;University Key Lab of Information Science & Engineering, Dalian University, Dalian, China
Venue:
IWANN'05 Proceedings of the 8th international conference on Artificial Neural Networks: computational Intelligence and Bioinspired Systems
Year:
2005

Citing 6
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Abstract

Global exponential stability of cellular neural networks with time-varying coefficients and delays is considered in this paper. By utilizing a delay differential inequality, a new sufficient condition ensuring global exponential stability for cellular neural networks with time-varying coefficients and delays is presented. Since the condition does not require that the delay function be differentiable or the coefficients be bounded, the results here improve and extend those given in the earlier literature.