DocumentCode
3345273
Title
Globally Exponential Stability of Neural Networks with Impulses and Distributed Delays
Author
Yang, Jianfu ; Liu, Ren ; Yang, Fengjian ; Li, Wei ; Wu, Dongqing
Author_Institution
Dept. of Comput. Sci., Zhongkai Univ. of Agric. & Eng., Guangzhou, China
fYear
2009
fDate
14-17 Oct. 2009
Firstpage
472
Lastpage
475
Abstract
In this paper, the main purpose is to study the global exponential stability of the equilibrium point for a class of cellular neural networks with impulses and distributed delays. With the assumption of global Lipschitz conditions on the activation function, applying idea of vector Lyapunov function, combining Halanay differential inequality with delay, a sufficient condition for globally exponential stability of neural networks is obtained.
Keywords
Lyapunov methods; asymptotic stability; delays; neural nets; transfer functions; Halanay differential inequality; Lyapunov function; activation function; global Lipschitz conditions; neural network distributed delays; neural network globally exponential stability; neural network impulses; Agricultural engineering; Agriculture; Asymptotic stability; Cellular neural networks; Computer networks; Distributed computing; Genetics; Kernel; Lyapunov method; Neural networks; global exponential stability;
fLanguage
English
Publisher
ieee
Conference_Titel
Genetic and Evolutionary Computing, 2009. WGEC '09. 3rd International Conference on
Conference_Location
Guilin
Print_ISBN
978-0-7695-3899-0
Type
conf
DOI
10.1109/WGEC.2009.33
Filename
5402792
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