Title :
Almost surely asymptotic stability of neutral stochastic neural networks with multiple time-varying delays
Author :
Tan, Weiming ; Huang, Z.T. ; Qin, X.W.
Author_Institution :
Sch. of Math. & Phys., Wuzhou Univ., Wuzhou, China
Abstract :
In this paper, we study the almost surely asymptotic stability of neutral stochastic neural networks with multiple time-varying delays. By using Lyapunov-Krasovskii and linear matrix inequality approach, we obtain some sufficient conditions to ensure the stability of neutral stochastic neural networks. The results are show to be generalizations of some previously published results and are less conservative than existing results.
Keywords :
Lyapunov methods; asymptotic stability; linear matrix inequalities; neurocontrollers; stochastic systems; Lyapunov-Krasovskii approach; asymptotic stability; linear matrix inequality; multiple time-varying delays; neutral stochastic neural network; Asymptotic stability; Biological neural networks; Circuit stability; Delay; Stability criteria; Almost surely asymptotic stability; Linear matrix inequality; Lyapunov functional; Multiple time-varying delays; Neutral stochastic neural networks;
Conference_Titel :
Mechanic Automation and Control Engineering (MACE), 2011 Second International Conference on
Conference_Location :
Hohhot
Print_ISBN :
978-1-4244-9436-1
DOI :
10.1109/MACE.2011.5986857
