Improved multiexponential transient spectroscopy by iterative deconvolution

dc.contributor.authorMarco Colás, Santiagocat
dc.contributor.authorPalacín Roca, Jordicat
dc.contributor.authorSamitier i Martí, Josepcat
dc.date.accessioned2009-06-18T08:28:33Z
dc.date.available2009-06-18T08:28:33Z
dc.date.issued2001cat
dc.description.abstractThe analysis of multiexponential decays is challenging because of their complex nature. When analyzing these signals, not only the parameters, but also the orders of the models, have to be estimated. We present an improved spectroscopic technique specially suited for this purpose. The proposed algorithm combines an iterative linear filter with an iterative deconvolution method. A thorough analysis of the noise effect is presented. The performance is tested with synthetic and experimental data.eng
dc.format.extent7 p.cat
dc.format.mimetypeapplication/pdfeng
dc.identifier.idgrec176004cat
dc.identifier.issn0018-9456cat
dc.identifier.urihttps://hdl.handle.net/2445/8723
dc.language.isoengeng
dc.publisherIEEEcat
dc.relation.isformatofReproducció del document publicat a http://dx.doi.org/10.1109/19.930453ca
dc.relation.ispartofIEEE Transactions on Instrumentation and Measurement, 2001, vol. 50, núm. 3, p. 774-780.eng
dc.relation.urihttp://dx.doi.org/10.1109/19.930453
dc.rights(c) IEEE, 2001cat
dc.rights.accessRightsinfo:eu-repo/semantics/openAccess
dc.sourceArticles publicats en revistes (Enginyeria Electrònica i Biomèdica)
dc.subject.classificationEspectroscòpia electrònicacat
dc.subject.classificationMínims quadratscat
dc.subject.otherGaussian noiseeng
dc.subject.otherLaplace transformseng
dc.subject.otherCurve fittingeng
dc.subject.otherDeconvolutioneng
dc.subject.otherDeep level transient spectroscopyeng
dc.subject.otherDiscrete time filterseng
dc.subject.otherExponential distributioneng
dc.subject.otherIterative methodseng
dc.subject.otherLeast squareseng
dc.subject.otherApproximationseng
dc.subject.otherSpectroscopy computingeng
dc.titleImproved multiexponential transient spectroscopy by iterative deconvolutioneng
dc.typeinfo:eu-repo/semantics/articlecat
dc.typeinfo:eu-repo/semantics/publishedVersion

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