Title :
Global Exponential Stability of Impulsive Static Neural Networks with Time-Varying Delays
Author :
Zhao, Yongchang ; Wang, Linshan
Author_Institution :
Coll. of Inf. Sci. & Eng., Ocean Univ. of China, Qingdao, China
Abstract :
This paper investigates the global exponential stability of static neural networks (SNN) with time-varying delays and fixed moments of impulsive effect. Sufficient conditions for the exponential stability are established by using Lyapunov functions and the Razumikhin technique.
Keywords :
Lyapunov methods; asymptotic stability; delay systems; neurocontrollers; time-varying systems; Lyapunov function; Razumikhin technique; global exponential stability; impulsive effect; impulsive static neural network; time-varying delay; Delay effects; Educational institutions; Electronic mail; Information science; Mathematical model; Neural networks; Neurons; Oceans; Recurrent neural networks; Stability; global exponential stability; impulsive; static neural networks; time-varying delay;
Conference_Titel :
Computer Sciences and Convergence Information Technology, 2009. ICCIT '09. Fourth International Conference on
Conference_Location :
Seoul
Print_ISBN :
978-1-4244-5244-6
Electronic_ISBN :
978-0-7695-3896-9
DOI :
10.1109/ICCIT.2009.163
