A novel adaptive filter algorithm for tracking of chaotic time series

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dc.contributor.authorMengüç, Engin Cemal
dc.contributor.authorAcir, Nurettin
dc.date.accessioned2024-11-07T10:39:27Z
dc.date.available2024-11-07T10:39:27Z
dc.date.issued2011
dc.departmentNiğde Ömer Halisdemir Üniversitesi
dc.description2011 IEEE 19th Signal Processing and Communications Applications Conference, SIU 2011 -- 20 April 2011 through 22 April 2011 -- Antalya -- 85528
dc.description.abstractIn this study, a novel tracking filter algorithm is proposed satisfying stability in the sense of Lyapunov and is performed which is independent of statistical properties of input. The robustness of the proposed filter is presented by using two benchmark chaotic time series found in the literature. The proposed filter is compared with well known classical filters and performed in a high performance. © 2011 IEEE.
dc.identifier.doi10.1109/SIU.2011.5929695
dc.identifier.endpage493
dc.identifier.isbn978-145770463-5
dc.identifier.scopus2-s2.0-79960388818
dc.identifier.scopusqualityN/A
dc.identifier.startpage490
dc.identifier.urihttps://doi.org/10.1109/SIU.2011.5929695
dc.identifier.urihttps://hdl.handle.net/11480/10980
dc.indekslendigikaynakScopus
dc.language.isotr
dc.relation.ispartof2011 IEEE 19th Signal Processing and Communications Applications Conference, SIU 2011
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_20241106
dc.subjectAdaptive filters
dc.subjectSignal processing
dc.subjectTime series
dc.subjectChaotic time series
dc.subjectClassical filters
dc.subjectFilter algorithm
dc.subjectLyapunov
dc.subjectStatistical properties
dc.subjectTracking filter
dc.subjectAdaptive algorithms
dc.titleA novel adaptive filter algorithm for tracking of chaotic time series
dc.title.alternativeKaoti?k zaman seri?leri?ni? i?zlemek i?çi?n yeni? bi?r adapti?f fi?ltre algori?tmasi
dc.typeConference Object

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