Gaussian and Golden Wavelets: A Comparative Study and their Applications in Structural Health Monitoring

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dc.contributor.authorGossler, F. E. [UNESP]
dc.contributor.authorOliveira, B. R. [UNESP]
dc.contributor.authorDuarte, M. A. Q.
dc.contributor.authorVieira, J. [UNESP]
dc.contributor.authorVillarreal, F. [UNESP]
dc.contributor.authorLamblém, R. L.
dc.contributor.institutionUniversidade Estadual Paulista (Unesp)
dc.contributor.institutionMato Grosso do Sul State University
dc.date.accessioned2021-07-14T10:37:15Z
dc.date.available2021-07-14T10:37:15Z
dc.date.issued2021-04-05
dc.description.abstractIn this work, a comparative analysis between Gaussian and Golden wavelets is presented. These wavelets are generated by the derivative of specific base functions. In this case, the order of the derivative also indicates the number of vanishing moments of the wavelet. Although these wavelets have a similar waveform, they have several distinct characteristics in time and frequency domains. These distinctions are explored here in the scale space. In order to compare the results provided by these wavelets for a real signal, they are used in the decomposition of a signal inserted in the context of structural health monitoring.en
dc.description.abstractNeste trabalho, uma análise comparativa entre as wavelets Gaussianas e Golden é apresentada. Tais wavelets são geradas pela derivada de uma função basica específica. Nesse caso, a ordem da derivada também indica o número de momentos nulos da wavelet. Embora essas wavelets tenham formas de onda muito semelhantes, elas possuem várias características distintas nos domínios do tempo e da frequência. Essas distinções são exploradas aqui no espaço de escalas. A fim de comparar os resultados das wavelets para um sinal real, essas wavelets são usadas na decomposição de um sinal inserido no contexto do sistemas de monitoramento de integridade estrutural.pt
dc.description.affiliationSão Paulo State University, Department of Electrical Engineering
dc.description.affiliationMato Grosso do Sul State University, Department of Mathematics
dc.description.affiliationSão Paulo State University, Department of Mathematics
dc.description.affiliationUnespSão Paulo State University, Department of Electrical Engineering
dc.description.affiliationUnespSão Paulo State University, Department of Mathematics
dc.format.extent139-155
dc.identifierhttp://dx.doi.org/10.5540/tcam.2021.022.01.00139
dc.identifier.citationTrends in Computational and Applied Mathematics. Sociedade Brasileira de Matemática Aplicada e Computacional - SBMAC, v. 22, n. 1, p. 139-155, 2021.
dc.identifier.doi10.5540/tcam.2021.022.01.00139
dc.identifier.fileS2676-00292021000100139.pdf
dc.identifier.issn2676-0029
dc.identifier.scieloS2676-00292021000100139
dc.identifier.urihttp://hdl.handle.net/11449/212269
dc.language.isoeng
dc.publisherSociedade Brasileira de Matemática Aplicada e Computacional - SBMAC
dc.relation.ispartofTrends in Computational and Applied Mathematics
dc.rights.accessRightsAcesso aberto
dc.sourceSciELO
dc.subjectgaussian waveletsen
dc.subjectgolden waveletsen
dc.subjectvanishing momentsen
dc.subjectstructural health monitoringen
dc.subjectwavelets gaussianapt
dc.subjectwavelets goldenpt
dc.subjectmomentos nulospt
dc.subjectmonitoramento de integridade estruturalpt
dc.titleGaussian and Golden Wavelets: A Comparative Study and their Applications in Structural Health Monitoringen
dc.typeArtigo
unesp.author.orcid0000-0001-5095-1363[1]
unesp.author.orcid0000-0002-1037-6541[2]
unesp.author.orcid0000-0003-2494-448X[3]
unesp.author.orcid0000-0003-1274-5424[4]
unesp.author.orcid0000-0001-8218-8593[5]
unesp.author.orcid0000-0002-6354-7375[6]

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