Title :
Global exponential stability in Lagrange sense for a class of neural networks with reaction-diffusion terms
Author :
Luo Qi ; Zhang Yutian
Author_Institution :
Coll. of Inf. & Control, Nanjing Univ. of Inf. Sci. & Technol., Nanjing, China
Abstract :
With considering two types of bounded activation functions, the global exponential stability in Lagrange sense are considered for Cohen-Grossberg neural networks with time-varying delays and reaction-diffusion terms. By employing appropriate Lyapunov functions, Green formula and inequality techniques, several global exponential attractive sets are given in which all trajectories converge. The obtained results can also be applied to analyse monostable as well as multistable neural networks.
Keywords :
asymptotic stability; delays; neural nets; reaction-diffusion systems; time-varying systems; transfer functions; Cohen-Grossberg neural networks; Green formula; Lagrange sense; appropriate Lyapunov functions; bounded activation functions; global exponential attractive sets; global exponential stability; inequality techniques; monostable neural networks; multistable neural networks; reaction-diffusion terms; time-varying delays; Artificial neural networks; Asymptotic stability; Circuit stability; Electronic mail; Stability criteria; Cohen-Grossberg Neural Network; Global Exponential Stability; Neutral Type; Time Delay;
Conference_Titel :
Control Conference (CCC), 2011 30th Chinese
Conference_Location :
Yantai
Print_ISBN :
978-1-4577-0677-6
Electronic_ISBN :
1934-1768
