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Article: Noise level estimation for a chaotic time series

TitleNoise level estimation for a chaotic time series
Authors
KeywordsChaotic time series
correlation integral
noise level
Issue Date2012
PublisherWorld Scientific Publishing Co Pte Ltd. The Journal's web site is located at http://www.worldscinet.com/ijbc/ijbc.shtml
Citation
International Journal Of Bifurcation And Chaos, 2012, v. 22 n. 3, article no. 1250052 How to Cite?
AbstractIn this study, the correlation sum and the correlation integral for chaotic time series using the Supremum norm and the Euclidean norm are discussed. The correlation integrals are then used to develop governing equations for the correlation sum, noise level and correlation dimension in which the correlation dimension and the noise level are linearly dependent on each other. Some linear estimation methods for the noise level are then introduced by using these equations. The estimation methods are applied to four chaotic time series (two artificial and two real-world). By comparing the performances of the estimations of the noise level, the best estimating method is then suggested. © 2012 World Scientific Publishing Company.
Persistent Identifierhttp://hdl.handle.net/10722/159908
ISSN
2015 Impact Factor: 1.355
2015 SCImago Journal Rankings: 0.789
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorXu, Pen_HK
dc.contributor.authorLi, WKen_HK
dc.contributor.authorJayawardena, AWen_HK
dc.date.accessioned2012-08-16T05:59:11Z-
dc.date.available2012-08-16T05:59:11Z-
dc.date.issued2012en_HK
dc.identifier.citationInternational Journal Of Bifurcation And Chaos, 2012, v. 22 n. 3, article no. 1250052en_HK
dc.identifier.issn0218-1274en_HK
dc.identifier.urihttp://hdl.handle.net/10722/159908-
dc.description.abstractIn this study, the correlation sum and the correlation integral for chaotic time series using the Supremum norm and the Euclidean norm are discussed. The correlation integrals are then used to develop governing equations for the correlation sum, noise level and correlation dimension in which the correlation dimension and the noise level are linearly dependent on each other. Some linear estimation methods for the noise level are then introduced by using these equations. The estimation methods are applied to four chaotic time series (two artificial and two real-world). By comparing the performances of the estimations of the noise level, the best estimating method is then suggested. © 2012 World Scientific Publishing Company.en_HK
dc.languageengen_US
dc.publisherWorld Scientific Publishing Co Pte Ltd. The Journal's web site is located at http://www.worldscinet.com/ijbc/ijbc.shtmlen_HK
dc.relation.ispartofInternational Journal of Bifurcation and Chaosen_HK
dc.subjectChaotic time seriesen_HK
dc.subjectcorrelation integralen_HK
dc.subjectnoise levelen_HK
dc.titleNoise level estimation for a chaotic time seriesen_HK
dc.typeArticleen_HK
dc.identifier.emailXu, P: xupc@amss.ac.cnen_HK
dc.identifier.emailLi, WK: hrntlwk@hku.hk-
dc.identifier.authorityLi, WK=rp00741en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1142/S0218127412500526en_HK
dc.identifier.scopuseid_2-s2.0-84859836838en_HK
dc.identifier.hkuros204207en_US
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-84859836838&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume22en_HK
dc.identifier.issue3, article no. 1250052en_HK
dc.identifier.isiWOS:000303206700012-
dc.publisher.placeSingaporeen_HK
dc.identifier.scopusauthoridXu, P=8440784800en_HK
dc.identifier.scopusauthoridLi, WK=14015971200en_HK
dc.identifier.scopusauthoridJayawardena, AW=7005049253en_HK

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