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dc.contributor.authorMader, Wolfgang
dc.contributor.authorLinke, Yannick
dc.contributor.authorMader, Malenka
dc.contributor.authorSommerlade, Linda
dc.contributor.authorTimmer, Jens
dc.contributor.authorSchelter, Bjoern
dc.date.accessioned2015-03-17T14:29:00Z
dc.date.available2015-03-17T14:29:00Z
dc.date.issued2014-08-15
dc.identifier.citationMader , W , Linke , Y , Mader , M , Sommerlade , L , Timmer , J & Schelter , B 2014 , ' A numerically efficient implementation of the expectation maximization algorithm for state space models ' , Applied Mathematics and Computation , vol. 241 , pp. 222-232 . https://doi.org/10.1016/j.amc.2014.05.021en
dc.identifier.issn0096-3003
dc.identifier.otherPURE: 48634397
dc.identifier.otherPURE UUID: adf6c229-6336-43c6-a65f-a4c8f84602ef
dc.identifier.otherWOS: 000338734700023
dc.identifier.otherScopus: 84901951046
dc.identifier.urihttp://hdl.handle.net/2164/4320
dc.format.extent11
dc.language.isoeng
dc.relation.ispartofApplied Mathematics and Computationen
dc.rightsNOTICE: this is the author’s version of a work that was accepted for publication in Applied Mathematics and Computation. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Applied Mathematics and Computation VOL 241, (2014) DOI: 10.1016/j.amc.2014.05.021en
dc.subjectKalman filteren
dc.subjectexpectation-maximization algorithmen
dc.subjectparameter estimationen
dc.subjectstate-space modelen
dc.subjectmaximum-likelihooden
dc.subjectsystemsen
dc.subjectQC Physicsen
dc.subject.lccQCen
dc.titleA numerically efficient implementation of the expectation maximization algorithm for state space modelsen
dc.typeJournal articleen
dc.contributor.institutionUniversity of Aberdeen.Physicsen
dc.contributor.institutionUniversity of Aberdeen.Institute for Complex Systems and Mathematical Biology (ICSMB)en
dc.contributor.institutionUniversity of Aberdeen.Mathematical Sciences (Research Theme)en
dc.description.statusPeer revieweden
dc.description.versionPostprinten
dc.identifier.doihttps://doi.org/10.1016/j.amc.2014.05.021


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