dc.contributorUniversidade Estadual Paulista (Unesp)
dc.contributorTecnológica Paula Souza (CEETEPS)
dc.contributorUniversidade de São Paulo (USP)
dc.date.accessioned2021-06-25T11:04:50Z
dc.date.accessioned2022-12-19T22:35:52Z
dc.date.available2021-06-25T11:04:50Z
dc.date.available2022-12-19T22:35:52Z
dc.date.created2021-06-25T11:04:50Z
dc.date.issued2020-01-01
dc.identifierInternational Journal of Wavelets, Multiresolution and Information Processing.
dc.identifier0219-6913
dc.identifierhttp://hdl.handle.net/11449/208009
dc.identifier10.1142/S0219691320300017
dc.identifier2-s2.0-85091873872
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/5388606
dc.description.abstractWavelets have been placed at the forefront of scientific researches involving signal processing, applied mathematics, pattern recognition and related fields. Nevertheless, as we have observed, students and young researchers still make mistakes when referring to one of the most relevant tools for time-frequency signal analysis. Thus, this correspondence clarifies the terminologies and specific roles of four types of wavelet transforms: The continuous wavelet transform (CWT), the discrete wavelet transform (DWT), the discrete-time wavelet transform (DTWT) and the stationary discrete-time wavelet transform (SDTWT). We believe that, after reading this correspondence, readers will be able to correctly refer to, and identify, the most appropriate type of wavelet transform for a certain application, selecting relevant and accurate material for subsequent investigation.
dc.languageeng
dc.relationInternational Journal of Wavelets, Multiresolution and Information Processing
dc.sourceScopus
dc.subjectContinuous wavelet transform
dc.subjectdiscrete wavelet transform
dc.subjectdiscrete-time wavelet transform
dc.subjectstationary discrete-time wavelet transform
dc.subjectwavelet applications
dc.titleCWT x DWT x DTWT x SDTWT: Clarifying terminologies and roles of different types of wavelet transforms
dc.typeOtros


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