Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/5266
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dc.contributorDepartment of Electronic and Information Engineering-
dc.creatorJudd, K-
dc.creatorNakamura, T-
dc.date.accessioned2014-12-11T08:29:02Z-
dc.date.available2014-12-11T08:29:02Z-
dc.identifier.issn1054-1500-
dc.identifier.urihttp://hdl.handle.net/10397/5266-
dc.language.isoenen_US
dc.publisherAmerican Institute of Physicsen_US
dc.rights© 2006 American Institute of Physics. This article may be downloaded for personal use only. Any other use requires prior permission of the author and the American Institute of Physics. The following article appeared in K. Judd & T. Nakamura, Chaos: an interdisciplinary journal of nonlinear science 16, 033105 (2006) and may be found at http://link.aip.org/link/?cha/16/033105en_US
dc.subjectTimes seriesen_US
dc.subjectNonlinear dynamical systemsen_US
dc.subjectChaosen_US
dc.subjectPolynomialsen_US
dc.titleDegeneracy of time series models : the best model is not always the correct modelen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.spage1-
dc.identifier.epage3-
dc.identifier.volume16-
dc.identifier.issue3-
dc.identifier.doi10.1063/1.2213957-
dcterms.abstractThere are a number of good techniques for finding, in some sense, the best model of a deterministic system given a time series of observations. We examine a problem called model degeneracy, which has the consequence that even when a perfect model of a system exists, one does not find it using the best techniques currently available. The problem is illustrated using global polynomial models and the theory of Gröbner bases.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationChaos, Sept. 2006, v. 16, no. 3, 033105, p. 1-3-
dcterms.isPartOfChaos-
dcterms.issued2006-09-
dc.identifier.isiWOS:000240876100005-
dc.identifier.scopus2-s2.0-33749343348-
dc.identifier.eissn1089-7682-
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumberOA_IR/PIRAen_US
dc.description.pubStatusPublisheden_US
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