Title :
New delay-dependent robust stability criterion for neutral stochastic neural networks with time delays
Author :
Qing, Qiu-ji ; He, Hai-kuo ; Xi, Duo-Ming ; Lu, Ji-Yong
Author_Institution :
Coll. of Sci., Hebei Univ. of Sci. & Technol., Shijiazhuang, China
Abstract :
In this paper, the problem of delay-dependent robust stability for uncertain neutral stochastic neural networks with time delays is considered. Based on Lyapunov stability theory combined with linear matrix inequalities (LMIs) techniques, some new delay-dependent stability conditions in terms of LMIs are derived by introducing some free weighting matrices and using Leibniz-Newton formula which can be selected properly to lead to less conservative results. Finally, a numerical example is given to illustrate the feasibility and effectiveness of the results.
Keywords :
Lyapunov methods; delays; linear matrix inequalities; neural nets; robust control; stochastic systems; uncertain systems; Leibniz-Newton formula; Lyapunov stability theory; delay-dependent robust stability criterion; delay-dependent stability conditions; free weighting matrices; linear matrix inequalities techniques; time delays; uncertain neutral stochastic neural networks; Cybernetics; Delay effects; Machine learning; Neural networks; Robust stability; Stochastic processes; Neutral; delay-dependent; neural networks; robust stability; stochastic;
Conference_Titel :
Machine Learning and Cybernetics, 2009 International Conference on
Conference_Location :
Baoding
Print_ISBN :
978-1-4244-3702-3
Electronic_ISBN :
978-1-4244-3703-0
DOI :
10.1109/ICMLC.2009.5212419