Global robust stability for delayed neural networks with polytopic type uncertainties

In this paper, global robust stability for delayed neural networks is studied. First the free-weighting matrices are employed to express the relationship between the terms in the system equation, and a stability condition for delayed neural networks is derived by using the S-procedure. Then this res...

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Bibliographic Details
Published in:Chaos, solitons and fractals solitons and fractals, 2005-12, Vol.26 (5), p.1349-1354
Main Authors: He, Yong, Wang, Qing-Guo, Zheng, Wei-Xing
Format: Article
Language:English
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Summary:In this paper, global robust stability for delayed neural networks is studied. First the free-weighting matrices are employed to express the relationship between the terms in the system equation, and a stability condition for delayed neural networks is derived by using the S-procedure. Then this result is extended to establish a global robust stability criterion for delayed neural networks with polytopic type uncertainties. A numerical example given in [IEEE Trans Circuits Syst II 52 (2005) 33–36] for interval delayed neural networks is investigated. The effectiveness of the presented global robust stability criterion and its improvement over the existing results are demonstrated.
ISSN:0960-0779
1873-2887
DOI:10.1016/j.chaos.2005.04.005