NDLI: New global stability criteria of neural networks with time delays

Content Provider	IEEE Xplore Digital Library
Author	Degang Yang Chunyan Hu Zhengxia Wang Xinyuan Liang
Copyright Year	2008
Description	Author affiliation: Coll. of Math. & Comput. Sci., Normal Univ., Chongqing (Degang Yang; Chunyan Hu)
Abstract	This paper studies global asymptotic stability of a general class of neural networks with time delays by utilizing Razumikhin theorem and the linear matrix inequality technique. Distinct difference from other analytical approaches lies in ldquolinearizationrdquo of the neural network model, by which the considered neural network model is transformed into a linear time-variant system. New sufficient conditions ensuring global asymptotic stability of the unique equilibrium point of delayed neural networks are obtained. The obtained conditions show to be less conservative and restrictive than those reported in the literature. A numerical simulation is given to illustrate the validity of our results.
Starting Page	5317
Ending Page	5320
File Size	113551
Page Count	4
File Format	PDF
ISBN	9781424421138
DOI	10.1109/WCICA.2008.4593795
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-06-25
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Artificial neural networks Asymptotic stability Stability analysis Stability criteria Delay effects Cellular neural networks Linear matrix inequalities Razumikhin theorem neural networks time delay stability linear matrix inequality
Content Type	Text
Resource Type	Article

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