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Article: A new stability criterion for discrete-time neural networks: Nonlinear spectral radius

TitleA new stability criterion for discrete-time neural networks: Nonlinear spectral radius
Authors
Mak, KLPeng, JGXu, ZBYiu, KFC
Issue Date2007
PublisherPergamon. The Journal's web site is located at http://www.elsevier.com/locate/chaos
Citation
Chaos, Solitons And Fractals, 2007, v. 31 n. 2, p. 424-436 How to Cite?
DOI: http://dx.doi.org/10.1016/j.chaos.2005.09.075
AbstractIn this paper, the exponential stability of nonlinear discrete-time systems is studied. A novel notion of nonlinear spectral radius is defined. Under the assumption of Lipschitz continuity for the activation function, the developed approach is applied to stability analysis of discrete-time neural networks. A series of sufficient conditions for global exponential stability of the neural networks are established and an estimate of the exponential decay rate is also derived for each case. © 2005 Elsevier Ltd. All rights reserved.
Persistent Identifierhttp://hdl.handle.net/10722/74354
ISSN
0960-0779
2021 Impact Factor: 9.922
2020 SCImago Journal Rankings: 1.043
ISI Accession Number ID
WOS:000240893400018
References
References in Scopus

 

DC FieldValueLanguage
dc.contributor.authorMak, KLen_HK
dc.contributor.authorPeng, JGen_HK
dc.contributor.authorXu, ZBen_HK
dc.contributor.authorYiu, KFCen_HK
dc.date.accessioned2010-09-06T07:00:31Z-
dc.date.available2010-09-06T07:00:31Z-
dc.date.issued2007en_HK
dc.identifier.citationChaos, Solitons And Fractals, 2007, v. 31 n. 2, p. 424-436en_HK
dc.identifier.issn0960-0779en_HK
dc.identifier.urihttp://hdl.handle.net/10722/74354-
dc.description.abstractIn this paper, the exponential stability of nonlinear discrete-time systems is studied. A novel notion of nonlinear spectral radius is defined. Under the assumption of Lipschitz continuity for the activation function, the developed approach is applied to stability analysis of discrete-time neural networks. A series of sufficient conditions for global exponential stability of the neural networks are established and an estimate of the exponential decay rate is also derived for each case. © 2005 Elsevier Ltd. All rights reserved.en_HK
dc.languageengen_HK
dc.publisherPergamon. The Journal's web site is located at http://www.elsevier.com/locate/chaosen_HK
dc.relation.ispartofChaos, Solitons and Fractalsen_HK
dc.titleA new stability criterion for discrete-time neural networks: Nonlinear spectral radiusen_HK
dc.typeArticleen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=0960-0779&volume=31&spage=424&epage=436&date=2007&atitle=A+new+stability+criterion+for+discrete-time+neural+networks:+nonlinear+spectral+radiusen_HK
dc.identifier.emailMak, KL:makkl@hkucc.hku.hken_HK
dc.identifier.emailYiu, KFC:cedric@hkucc.hku.hken_HK
dc.identifier.authorityMak, KL=rp00154en_HK
dc.identifier.authorityYiu, KFC=rp00206en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1016/j.chaos.2005.09.075en_HK
dc.identifier.scopuseid_2-s2.0-33745993334en_HK
dc.identifier.hkuros137072en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-33745993334&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume31en_HK
dc.identifier.issue2en_HK
dc.identifier.spage424en_HK
dc.identifier.epage436en_HK
dc.identifier.isiWOS:000240893400018-
dc.publisher.placeUnited Kingdomen_HK
dc.identifier.scopusauthoridMak, KL=7102680226en_HK
dc.identifier.scopusauthoridPeng, JG=7401959175en_HK
dc.identifier.scopusauthoridXu, ZB=7405426248en_HK
dc.identifier.scopusauthoridYiu, KFC=24802813000en_HK
dc.identifier.issnl0960-0779-

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