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dc.contributor.authorZimmermann, Boris
dc.contributor.authorKohler, Achim
dc.date.accessioned2018-04-05T10:38:16Z
dc.date.available2018-04-05T10:38:16Z
dc.date.created2013-09-20T14:35:23Z
dc.date.issued2013
dc.identifier.citationApplied Spectroscopy. 2013, 67 (8), 892-902.nb_NO
dc.identifier.issn0003-7028
dc.identifier.urihttp://hdl.handle.net/11250/2492789
dc.description.abstractCalculating derivatives of spectral data by the Savitzky–Golay (SG)numerical algorithm is often used as a preliminary preprocessing step to resolve overlapping signals, enhance signal properties, and suppress unwanted spectral features that arise due to nonideal instrument and sample properties. Addressing these issues, a study of the simulated and measured infrared data by partial least-squares regression has been conducted. The simulated data sets were modeled by considering a range of undesired chemical and physical spectral anomalies and variations that can occur in a measured spectrum, such as baseline variations, noise, and scattering effects. The study has demonstrated the importance of the optimization of the SG parameters during the conversion of spectra into derivative form, specifically window size and polynomial order of the fitting curve. A specific optimal window size is associated with an exact component of the system being estimated, and this window size does not necessarily apply for some other component present in the system. Since the optimization procedure can be time-consuming, as a rough guideline spectral noise level can be used for assessment of window size. Moreover,it has been demonstrated that, when the extended multiplicative signal correction (EMSC) is used alongside the SG procedure, the derivative treatment of data by the SG algorithm must precede the EMSC normalization.
dc.language.isoengnb_NO
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internasjonal*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/deed.no*
dc.titleOptimizing Savitzky-Golay Parameters for Improving Spectral Resolution and Quantification in Infrared Spectroscopynb_NO
dc.typeJournal articlenb_NO
dc.typePeer reviewednb_NO
dc.description.versionacceptedVersion
dc.source.pagenumber892-902nb_NO
dc.source.volume67nb_NO
dc.source.journalApplied Spectroscopynb_NO
dc.source.issue8nb_NO
dc.identifier.doi10.1366/12-06723
dc.identifier.cristin1050867
dc.relation.projectNorges forskningsråd: 199581nb_NO
dc.relation.projectNorges forskningsråd: 225347nb_NO
dc.relation.projectEgen institusjon: 201309nb_NO
dc.relation.projectEgen institusjon: 4049nb_NO
dc.relation.projectNorges forskningsråd: 225096nb_NO
dc.relation.projectEgen institusjon: 201302nb_NO
dc.relation.projectNorges forskningsråd: 216687nb_NO
cristin.unitcode192,15,0,0
cristin.unitnameRealfag og teknologi
cristin.ispublishedtrue
cristin.fulltextpostprint
cristin.qualitycode1


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Attribution-NonCommercial-NoDerivatives 4.0 Internasjonal
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