DocumentCode
478124
Title
Global Exponential Periodicity and Stability of a Class of Impulsive Neural Networks with Finite Distributed Delays
Author
Liu, Lechun ; Sun, Jianzhi
Author_Institution
Coll. of Sci., Yanshan Univ., Qinhuangdao
Volume
2
fYear
2008
fDate
18-20 Oct. 2008
Firstpage
399
Lastpage
403
Abstract
By constructing proper Lyapunov function and using some analysis techniques in the impulsive differential equation theory. A sufficient condition which ensures the global exponential periodicity and stability of neural networks with impulses and finite distributed delays is obtained. The obtained results in this paper improve and extend those given in the earlier literature.
Keywords
asymptotic stability; delays; differential equations; distributed control; neural nets; Lyapunov function; finite distributed delays; global exponential periodicity; impulsive differential equation theory; impulsive neural networks; stability; Cellular neural networks; Delay effects; Hopfield neural networks; Neural networks; Neurofeedback; Neurons; Output feedback; Stability; State feedback; Sufficient conditions; Finite distributed delay; Global exponential periodicity; Neural network; Stability;
fLanguage
English
Publisher
ieee
Conference_Titel
Natural Computation, 2008. ICNC '08. Fourth International Conference on
Conference_Location
Jinan
Print_ISBN
978-0-7695-3304-9
Type
conf
DOI
10.1109/ICNC.2008.856
Filename
4667025
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