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Delay-Dependent Exponential Stability of Neural Networks With Variable Delay: An LMI Approach

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4 Author(s)
Wu-Hua Chen ; Coll. of Math. & Inf. Sci., Guangxi Univ. ; Xiaomei Lu ; Zhi-Hong Guan ; Zheng, W.X.

This brief focuses on the problem of delay-dependent stability analysis of neural networks with variable delay. Two types of variable delay are considered: one is differentiable and has bounded derivative; the other one is continuous and may vary very fast. By introducing a new type of Lyapunov-Krasovskii functional, new delay-dependent sufficient conditions for exponential stability of delayed neural networks are derived in terms of linear matrix inequalities. We also obtain delay-independent stability criteria. Two examples are presented which show our results are less conservative than the existing stability criteria

Published in:

Circuits and Systems II: Express Briefs, IEEE Transactions on  (Volume:53 ,  Issue: 9 )

Date of Publication:

Sept. 2006

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