dc.creatorArruda, JRD
dc.date2010
dc.dateAPR
dc.date2014-07-30T13:42:46Z
dc.date2015-11-26T17:54:03Z
dc.date2014-07-30T13:42:46Z
dc.date2015-11-26T17:54:03Z
dc.date.accessioned2018-03-29T00:37:41Z
dc.date.available2018-03-29T00:37:41Z
dc.identifierMechanical Systems And Signal Processing. Academic Press Ltd- Elsevier Science Ltd, v. 24, n. 3, n. 835, n. 840, 2010.
dc.identifier0888-3270
dc.identifierWOS:000275097200019
dc.identifier10.1016/j.ymssp.2009.10.016
dc.identifierhttp://www.repositorio.unicamp.br/jspui/handle/REPOSIP/53710
dc.identifierhttp://repositorio.unicamp.br/jspui/handle/REPOSIP/53710
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/1290693
dc.descriptionConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
dc.descriptionFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
dc.descriptionThe regressive discrete Fourier series (RDFS) proposed in the early nineties can be used to smooth signals in one or two dimensions and to compute derivatives (e.g., spatial or time). This can be useful in applications where there is a need to compute derivatives of noisy data. The choice of the period and number of frequency lines of the Fourier series in the RDFS is empirical, based on the a priori information available about the data being treated. When the chosen period is larger that the data extension and the number of frequency lines increase, the RDFS may present numerical instability. In this paper a more robust RDFS is proposed to avoid such numerical instability. This robust version of the RDFS may be useful when a priori information is not available to guide the choice of the RDFS parameters. (C) 2009 Elsevier Ltd. All rights reserved.
dc.description24
dc.description3
dc.description835
dc.description840
dc.descriptionConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
dc.descriptionFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
dc.descriptionConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
dc.descriptionFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
dc.languageen
dc.publisherAcademic Press Ltd- Elsevier Science Ltd
dc.publisherLondon
dc.publisherInglaterra
dc.relationMechanical Systems And Signal Processing
dc.relationMech. Syst. Signal Proc.
dc.rightsfechado
dc.rightshttp://www.elsevier.com/about/open-access/open-access-policies/article-posting-policy
dc.sourceWeb of Science
dc.subjectData smoothing
dc.subjectRegression
dc.subjectFourier series
dc.subjectData derivatives
dc.subjectSpatially dense measurements
dc.titleA robust one-dimensional regressive discrete Fourier series
dc.typeArtículos de revistas


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