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dc.contributor.authorRamírez-Pacheco, Julio
dc.contributor.authorTorres-Román, Deni
dc.contributor.authorRizo-Domínguez, Luis
dc.contributor.authorTrejo-Sánchez, Joel
dc.contributor.authorManzano-Pinzón, Franciso
dc.date.accessioned2016-01-20T00:46:58Z
dc.date.accessioned2023-03-10T16:00:54Z
dc.date.available2016-01-20T00:46:58Z
dc.date.available2023-03-10T16:00:54Z
dc.date.issued2011-09
dc.identifier.citationRamírez-Pacheco, J.; Rizo-Domínguez, L., Torres-Román, D., Trejo Sánchez, J., Manzano-Pinzón, F. (2011). “Wavelet Fisher’s Information Measure of 1/fα signals”. Entropy Journal 13(9), pp 1648. Basel, Switzerland: MDPIes
dc.identifier.issn1099-4300
dc.identifier.otherdoi 10.3390/e13091648.
dc.identifier.urihttps://hdl.handle.net/20.500.12032/68329
dc.descriptionThis article defines the concept of wavelet-based Fisher’s information measure (wavelet FIM) and develops a closed-form expression of this measure for 1/fα signals. Wavelet Fisher’s information measure characterizes the complexities associated to 1/fα signals and provides a powerful tool for their analysis. Theoretical and experimental studies demonstrate that this quantity is exponentially increasing for α > 1 (non-stationary signals) and almost constant for α < 1 (stationary signals). Potential applications of wavelet FIM are discussed in some detail and its power and robustness for the detection of structural breaks in the mean embedded in stationary fractional Gaussian noise signals studied.es
dc.description.sponsorshipConsejo Nacional de Ciencia y Tecnologíaes
dc.description.sponsorshipFOMIX-COQCYTes
dc.language.isoenges
dc.publisherMDPIes
dc.relation.ispartofseriesEntropy;13(9)
dc.rights.urihttp://quijote.biblio.iteso.mx/licencias/CC-BY-NC-2.5-MX.pdfes
dc.subjectStructural Breakses
dc.subjectFisher Informationes
dc.subjectFractal Index Estimationes
dc.subjectFractional Gaussian Noisees
dc.titleWavelet Fisher’s Information Measure of 1=fα Signalses
dc.typeinfo:eu-repo/semantics/articlees


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