New Global Asymptotic Stability Criterion for Uncertain Neural Networks with Time-Varying and Distributed Delays

Authors:
Jiqing Qiu;Jinhui Zhang;Zhifeng Gao;Hongjiu Yang
Affiliations:
College of Sciences, Hebei University of Science and Technology, Shijiazhuang, Hebei 050018, P.R. China;College of Sciences, Hebei University of Science and Technology, Shijiazhuang, Hebei 050018, P.R. China;College of Sciences, Hebei University of Science and Technology, Shijiazhuang, Hebei 050018, P.R. China;College of Sciences, Hebei University of Science and Technology, Shijiazhuang, Hebei 050018, P.R. China
Venue:
ISNN '07 Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks
Year:
2007

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Abstract

This paper investigates the problem of global asymptoticstability for a class of uncertain neural networks with time-varying and distributed delays. The uncertainties we considered in this paper are norm-bounded, and possibly time-varying. By Lyapunov-Krasovskii functional approach and S-procedure, a new stability criteria for the asymptotic stability of the system is derived in terms of linear matrix inequalities (LMIs). Two simulation examples are given to demonstrate the effectiveness of the developed techniques.