A switching rule for exponential stability of switched recurrent neural networks with interval time-varying delay

This paper studies the problem for exponential stability of switched recurrent neural networks with interval time-varying delay. The time delay is a continuous function belonging to a given interval, but not necessarily differentiable. By constructing a set of argumented Lyapunov-Krasovskii function...

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Main Authors: Rajchakit M., Niamsup P., Rajchakit G.
Format: Article
Language:English
Published: 2014
Online Access:http://www.scopus.com/inward/record.url?eid=2-s2.0-84878629570&partnerID=40&md5=176925f6afb29f71c0b5f31c4dd416a1
http://cmuir.cmu.ac.th/handle/6653943832/7237
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Institution: Chiang Mai University
Language: English
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spelling th-cmuir.6653943832-72372014-08-30T03:51:43Z A switching rule for exponential stability of switched recurrent neural networks with interval time-varying delay Rajchakit M. Niamsup P. Rajchakit G. This paper studies the problem for exponential stability of switched recurrent neural networks with interval time-varying delay. The time delay is a continuous function belonging to a given interval, but not necessarily differentiable. By constructing a set of argumented Lyapunov-Krasovskii functionals combined with the Newton-Leibniz formula, a switching rule for exponential stability of switched recurrent neural networks with interval time-varying delay is designed via linear matrix inequalities, and new sufficient conditions for the exponential stability of switched recurrent neural networks with interval time-varying delay via linear matrix inequalities (LMIs) are derived. A numerical example is given to illustrate the effectiveness of the obtained result. © 2013 Rajchakit et al.; licensee Springer. 2014-08-30T03:51:43Z 2014-08-30T03:51:43Z 2013 Article 16871839 10.1186/1687-1847-2013-44 http://www.scopus.com/inward/record.url?eid=2-s2.0-84878629570&partnerID=40&md5=176925f6afb29f71c0b5f31c4dd416a1 http://cmuir.cmu.ac.th/handle/6653943832/7237 English
institution Chiang Mai University
building Chiang Mai University Library
country Thailand
collection CMU Intellectual Repository
language English
description This paper studies the problem for exponential stability of switched recurrent neural networks with interval time-varying delay. The time delay is a continuous function belonging to a given interval, but not necessarily differentiable. By constructing a set of argumented Lyapunov-Krasovskii functionals combined with the Newton-Leibniz formula, a switching rule for exponential stability of switched recurrent neural networks with interval time-varying delay is designed via linear matrix inequalities, and new sufficient conditions for the exponential stability of switched recurrent neural networks with interval time-varying delay via linear matrix inequalities (LMIs) are derived. A numerical example is given to illustrate the effectiveness of the obtained result. © 2013 Rajchakit et al.; licensee Springer.
format Article
author Rajchakit M.
Niamsup P.
Rajchakit G.
spellingShingle Rajchakit M.
Niamsup P.
Rajchakit G.
A switching rule for exponential stability of switched recurrent neural networks with interval time-varying delay
author_facet Rajchakit M.
Niamsup P.
Rajchakit G.
author_sort Rajchakit M.
title A switching rule for exponential stability of switched recurrent neural networks with interval time-varying delay
title_short A switching rule for exponential stability of switched recurrent neural networks with interval time-varying delay
title_full A switching rule for exponential stability of switched recurrent neural networks with interval time-varying delay
title_fullStr A switching rule for exponential stability of switched recurrent neural networks with interval time-varying delay
title_full_unstemmed A switching rule for exponential stability of switched recurrent neural networks with interval time-varying delay
title_sort switching rule for exponential stability of switched recurrent neural networks with interval time-varying delay
publishDate 2014
url http://www.scopus.com/inward/record.url?eid=2-s2.0-84878629570&partnerID=40&md5=176925f6afb29f71c0b5f31c4dd416a1
http://cmuir.cmu.ac.th/handle/6653943832/7237
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