DocumentCode :
179249
Title :
Global Exponential Stability of a Class of Variable Time-Delay Cellular Neural Networks
Author :
Zhang Changfan ; Zhang Miaoying ; Zhang Faming
Author_Institution :
Coll. of Electron. & Inf. Eng., Hunan Univ. of Technol., Zhuzhou, China
fYear :
2014
fDate :
15-16 June 2014
Firstpage :
517
Lastpage :
519
Abstract :
In view of variable time-delay cellular neural networks with activation function bounded and meeting the conditions of Lippschitz, the result of the global exponential stability is obtained by constructing a special Lyapunov function equality and using Lyapunov function technology and matrix inequality. The global exponential stability of variable time-delay cellular neural networks whose activation function is likewise linear function is discussed. An example and its computer simulation is given to prove the effectiveness of the obtained result. Finally the result of this paper is discussed by comparing existing achievements, and it is with advantage of low dimension validated matrix, simple calculation and easy computer implementation.
Keywords :
Lyapunov methods; asymptotic stability; cellular neural nets; delays; matrix algebra; activation function; computer simulation; global exponential stability; likewise linear function; matrix inequality; special Lyapunov function equality; variable time-delay cellular neural networks; Intelligent systems; Cellular neural networks; Lyapunov function; exponential stability;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Systems Design and Engineering Applications (ISDEA), 2014 Fifth International Conference on
Conference_Location :
Hunan
Print_ISBN :
978-1-4799-4262-6
Type :
conf
DOI :
10.1109/ISDEA.2014.122
Filename :
6977652
Link To Document :
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