Title :
Exponential robust stability of stochastic interval Hopfield neural networks with time-varying delays
Author_Institution :
Dept. of Math., Shanghai Univ., Shanghai
Abstract :
In this paper, the exponential robust stability for stochastic interval Hopfield neural networks with time-varying delays is investigated. Based on Lyapunov functional approach and linear matrix inequality (LMI) technique, the sufficient conditions are proposed to ensure stochastic interval Hopfield neural networks to be exponential robustly stable.
Keywords :
Hopfield neural nets; Lyapunov methods; delays; linear matrix inequalities; robust control; stability; stochastic systems; Lyapunov functional approach; exponential robust stability; linear matrix inequality; stochastic interval Hopfield neural networks; time-varying delays; Artificial neural networks; Biological neural networks; Delay effects; Hopfield neural networks; Linear matrix inequalities; Robust stability; Stability analysis; Stochastic processes; Stochastic systems; Sufficient conditions; Exponential robust stability; Linear matrix inequality (LMI); Lyapunov functional; Stochastic interval hopfield neural networks; Time-varying delays;
Conference_Titel :
Control Conference, 2008. CCC 2008. 27th Chinese
Conference_Location :
Kunming
Print_ISBN :
978-7-900719-70-6
Electronic_ISBN :
978-7-900719-70-6
DOI :
10.1109/CHICC.2008.4605578
