DocumentCode :
1188236
Title :
New Delay-Dependent Global Exponential Stability Criterion for Cellular-Type Neural Networks With Time-Varying Delays
Author :
Zheng, Cheng-De ; Zhang, Huaguang ; Wang, Zhanshan
Author_Institution :
Dept. of Math., Dalian Jiaotong Univ., Dalian
Volume :
56
Issue :
3
fYear :
2009
fDate :
3/1/2009 12:00:00 AM
Firstpage :
250
Lastpage :
254
Abstract :
The problem ensuring the global exponential stability (GES) of a class of delayed cellular neural networks (CNNs) with time-varying delays is studied. Without assuming the boundedness of the activation functions, by applying the idea of the Lyapunov function, the linear matrix inequality (LMI) techniques, the free-weighting matrix method, and a novel equation, a new sufficient condition for the GES of CNNs with time-varying delays is obtained, which generalizes the previous results in the literature. The criterion is easy to be verified since it takes the form of an LMI. Three numerical examples are given to illustrate the effectiveness and less conservativeness of our proposed method.
Keywords :
Lyapunov methods; asymptotic stability; cellular neural nets; delays; linear matrix inequalities; time-varying systems; Lyapunov function; cellular-type neural networks; delay-dependent global exponential stability criterion; delayed cellular neural networks; free-weighting matrix method; linear matrix inequality techniques; time-varying delays; Cellular neural networks (CNNs); global exponential stability (GES); linear matrix inequality (LMI); time-varying delays;
fLanguage :
English
Journal_Title :
Circuits and Systems II: Express Briefs, IEEE Transactions on
Publisher :
ieee
ISSN :
1549-7747
Type :
jour
DOI :
10.1109/TCSII.2008.2011594
Filename :
4799131
Link To Document :
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