Title :
Exponential Stability of Delayed High-order Hopfield-type Neural Networks with Diffusion
Author :
Xuyang, Lou ; Baotong, Cui
Author_Institution :
Southern Yangtze Univ., Wuxi
Abstract :
This paper considers a generalized model of high-order Hopfield-type neural networks with time-varying delays and reaction-diffusion terms. By using the method of Lyapunov function and Halanay´s inequality, we investigate the global exponential stability of high-order Hopfield-type neural networks with time-varying delays and reaction-diffusion terms. A sufficient condition for ensuring global exponential stability of these networks is derived, and the estimated exponential convergence rate is also obtained. As an illustration, an numerical example is worked out using the results obtained.
Keywords :
Hopfield neural nets; Lyapunov methods; asymptotic stability; delays; reaction-diffusion systems; Lyapunov function; delayed high-order Hopfield-type neural networks; global exponential stability; inequality; reaction-diffusion; time-varying delays; Convergence; Delay effects; Electronic mail; Hopfield neural networks; Lyapunov method; Neural networks; Neurons; Stability; Sufficient conditions; Symmetric matrices; Exponential stability; Lyapunov function; Neural networks; Reaction-diffusion terms; Time-varying delays;
Conference_Titel :
Control Conference, 2007. CCC 2007. Chinese
Conference_Location :
Hunan
Print_ISBN :
978-7-81124-055-9
Electronic_ISBN :
978-7-900719-22-5
DOI :
10.1109/CHICC.2006.4346841
