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dc.contributor.authorBrowne, Matthewen_US
dc.contributor.authorCutmore, Timothyen_US
dc.contributor.authorMayer, N.en_US
dc.date.accessioned2017-04-04T15:52:11Z
dc.date.available2017-04-04T15:52:11Z
dc.date.issued2007en_US
dc.identifier.issn10512004en_US
dc.identifier.doi10.1016/j.dsp.2006.01.006en_US
dc.identifier.urihttp://hdl.handle.net/10072/15641
dc.description.abstractThe effectiveness of Savitzky-Golay type symmetric polynomial smoothers is known to be strongly dependent on the window size. Many authors note that selection of the appropriate window size is essential for achieving the correct trade-off between noise reduction and avoiding the introduction of bias. However, it is often overlooked that, in the case of non-stationary signals, the optimal window size will vary with the dynamics of the signal. A multiresolution approach is outlined, along with criteria for varying window size with respect to translation, based on evaluation of the residuals of the smoothed data in the local region. Adaptive window polynomial smoothing is shown to be superior to fixed window smoothing for a test signal at various signal-tonoise ratios.en_US
dc.description.peerreviewedYesen_US
dc.description.publicationstatusYesen_US
dc.languageEnglishen_US
dc.language.isoen_US
dc.publisherAcademic Pressen_US
dc.publisher.placeUnited Statesen_US
dc.relation.ispartofstudentpublicationNen_US
dc.relation.ispartofpagefrom69en_US
dc.relation.ispartofpageto75en_US
dc.relation.ispartofjournalDigital Signal Processingen_US
dc.relation.ispartofvolume17en_US
dc.rights.retentionYen_US
dc.subject.fieldofresearchcode280204en_US
dc.subject.fieldofresearchcode280401en_US
dc.titleA multiscale polynomial filter for adaptive smoothingen_US
dc.typeJournal articleen_US
dc.type.descriptionC1 - Peer Reviewed (HERDC)en_US
dc.type.codeC - Journal Articlesen_US
gro.facultyGriffith Sciences, Griffith School of Environmenten_US
gro.date.issued2015-05-04T22:04:52Z
gro.hasfulltextNo Full Text


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