Stability of Cellular Neural Networks with Time Varying Delay

In this note, the global asymptotic stability of a class of delayed cellular neural networks is studied. Some new sufficient conditions are presented for the uniqueness of equilibrium point and the global stability of cellular neural networks with time varying delay by constructing Lyapunov function...

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Bibliographic Details
Main Authors: Pu Wang, Xueli Wu, Ran Zhen, Yanhong Wang
Format: Conference Proceeding
Language:English
Subjects:
Asymptotic stability
Cellular neural networks
Computer networks
Delay effects
Guidelines
Linear matrix inequalities
Radio access networks
Stability criteria
Sufficient conditions
Time varying systems
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Summary:In this note, the global asymptotic stability of a class of delayed cellular neural networks is studied. Some new sufficient conditions are presented for the uniqueness of equilibrium point and the global stability of cellular neural networks with time varying delay by constructing Lyapunov functional and using linear matrix inequality (LMI). A numerical example is presented to illustrate the effectiveness of our theoretical results.
ISSN:2157-9555
DOI:10.1109/ICNC.2008.537