dc.creatorTorres R.
dc.creatorTorres E.
dc.date.accessioned2020-03-26T16:32:54Z
dc.date.accessioned2022-09-28T20:08:43Z
dc.date.available2020-03-26T16:32:54Z
dc.date.available2022-09-28T20:08:43Z
dc.date.created2020-03-26T16:32:54Z
dc.date.issued2013
dc.identifierIEEE Transactions on Signal Processing; Vol. 61, Núm. 6; pp. 1555-1560
dc.identifier1053587X
dc.identifierhttps://hdl.handle.net/20.500.12585/9077
dc.identifier10.1109/TSP.2012.2236834
dc.identifierUniversidad Tecnológica de Bolívar
dc.identifierRepositorio UTB
dc.identifier56270896900
dc.identifier35094573000
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/3720813
dc.description.abstractIn this paper, a generalized notion of wide-sense α-stationarity for random signals is presented. The notion of stationarity is fundamental in the Fourier analysis of random signals. For this purpose, a definition of the fractional correlation between two random variables is introduced. It is shown that for wide-sense α-stationary random signals, the fractional correlation and the fractional power spectral density functions form a fractional Fourier transform pair. Thus, the concept of α-stationarity plays an important role in the analysis of random signals through the fractional Fourier transform for signals nonstationary in the standard formulation, but α-stationary. Furthermore, we define the α-Wigner-Ville distribution in terms of the fractional correlation function, in which the standard Fourier analysis is the particular case for α=pi2, and it leads to the Wiener-Khinchin theorem. © 1991-2012 IEEE.
dc.languageeng
dc.rightshttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.rightsinfo:eu-repo/semantics/restrictedAccess
dc.rightsAtribución-NoComercial 4.0 Internacional
dc.sourcehttps://www.scopus.com/inward/record.uri?eid=2-s2.0-84875015943&doi=10.1109%2fTSP.2012.2236834&partnerID=40&md5=8948c99af3dc2f6f9bcba86bcaee6a4d
dc.titleFractional Fourier analysis of random signals and the notion of α -Stationarity of the Wigner-Ville distribution


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