DocumentCode :
232405
Title :
Polystability in Lagrange sense for a class of delayed neural networks
Author :
Zhao Zhihua ; Jian Jigui ; Li Liangliang
Author_Institution :
Coll. of Sci., China Three Gorges Univ. Yichang, Yichang, China
fYear :
2014
fDate :
28-30 July 2014
Firstpage :
6099
Lastpage :
6102
Abstract :
In this paper, the polystability of a class of neural networks with constant delay is discussed. By constructing a new Lyapunov function, a delay-dependent criterion is obtained to ensure the system is bounded and exponentially bounded with respect to partial states. The result derived here generalizes and improves the earlier publications. Finally, one numerical example is given and analyzed to demonstrate our result..
Keywords :
Lyapunov methods; delays; neurocontrollers; stability; Lagrange sense; Lyapunov function; delay-dependent criterion; delayed neural networks; exponentially bounded system; polystability; Artificial neural networks; Educational institutions; Lyapunov methods; Numerical stability; Stability criteria; Delayed neural networks; Lyapunov function; inequality; polystability in Lagrange sense;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control Conference (CCC), 2014 33rd Chinese
Conference_Location :
Nanjing
Type :
conf
DOI :
10.1109/ChiCC.2014.6895987
Filename :
6895987
Link To Document :
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