DocumentCode
527689
Title
Exponential stability of impulsive Cohen-Grossberg-type BAM neural networks with delays and diffusion terms
Author
Wan, Li ; Zhou, Qinghua
Author_Institution
Coll. of Sci., Wuhan Textile Univ., Wuhan, China
Volume
1
fYear
2010
fDate
10-12 Aug. 2010
Firstpage
282
Lastpage
286
Abstract
This paper is concerned with impulsive Cohen-Grossberg-type BAM neural networks with time-varying delays and reaction-diffusion terms. By delay differential inequality with impulses, we present some sufficient conditions ensuring the global exponential stability of the equilibrium point. A numerical example is given to demonstrate the effectiveness and applicability of the proposed criteria.
Keywords
asymptotic stability; delay-differential systems; delays; neural nets; reaction-diffusion systems; time-varying systems; delay differential inequality; diffusion term; equilibrium point; exponential stability; impulsive Cohen-Grossberg type BAM neural network; reaction diffusion term; time varying delay; Artificial neural networks; Delay; Neurons; Numerical stability; Stability criteria;
fLanguage
English
Publisher
ieee
Conference_Titel
Natural Computation (ICNC), 2010 Sixth International Conference on
Conference_Location
Yantai, Shandong
Print_ISBN
978-1-4244-5958-2
Type
conf
DOI
10.1109/ICNC.2010.5583832
Filename
5583832
Link To Document