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dc.contributor.author
Traversaro Varela, Francisco
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dc.contributor.author
Redelico, Francisco Oscar
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dc.date.available
2019-12-26T16:18:33Z
dc.date.issued
2018-04
dc.identifier.citation
Traversaro Varela, Francisco; Redelico, Francisco Oscar; Confidence intervals and hypothesis testing for the Permutation Entropy with an application to epilepsy; Elsevier Science; Communications In Nonlinear Science And Numerical Simulation; 57; 4-2018; 388-401
dc.identifier.issn
1007-5704
dc.identifier.uri
http://hdl.handle.net/11336/92938
dc.description.abstract
In nonlinear dynamics, and to a lesser extent in other fields, a widely used measure of complexity is the Permutation Entropy. But there is still no known method to determine the accuracy of this measure. There has been little research on the statistical properties of this quantity that characterize time series. The literature describes some resampling methods of quantities used in nonlinear dynamics - as the largest Lyapunov exponent - but these seems to fail. In this contribution, we propose a parametric bootstrap methodology using a symbolic representation of the time series to obtain the distribution of the Permutation Entropy estimator. We perform several time series simulations given by well-known stochastic processes: the 1/fα noise family, and show in each case that the proposed accuracy measure is as efficient as the one obtained by the frequentist approach of repeating the experiment. The complexity of brain electrical activity, measured by the Permutation Entropy, has been extensively used in epilepsy research for detection in dynamical changes in electroencephalogram (EEG) signal with no consideration of the variability of this complexity measure. An application of the parametric bootstrap methodology is used to compare normal and pre-ictal EEG signals.
dc.format
application/pdf
dc.language.iso
eng
dc.publisher
Elsevier Science
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dc.rights
info:eu-repo/semantics/openAccess
dc.rights.uri
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.subject
EPILEPSY
dc.subject
HYPOTHESIS TEST
dc.subject
PERMUTATION ENTROPY
dc.subject.classification
Otras Ingenierías y Tecnologías
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dc.subject.classification
Otras Ingenierías y Tecnologías
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dc.subject.classification
INGENIERÍAS Y TECNOLOGÍAS
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dc.title
Confidence intervals and hypothesis testing for the Permutation Entropy with an application to epilepsy
dc.type
info:eu-repo/semantics/article
dc.type
info:ar-repo/semantics/artículo
dc.type
info:eu-repo/semantics/publishedVersion
dc.date.updated
2019-12-20T22:55:21Z
dc.journal.volume
57
dc.journal.pagination
388-401
dc.journal.pais
Países Bajos
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dc.journal.ciudad
Amsterdam
dc.description.fil
Fil: Traversaro Varela, Francisco. Universidad Nacional de Lanús; Argentina. Instituto Tecnológico de Buenos Aires; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
dc.description.fil
Fil: Redelico, Francisco Oscar. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Quilmes. Departamento de Ciencia y Tecnología; Argentina. Hospital Italiano; Argentina
dc.journal.title
Communications In Nonlinear Science And Numerical Simulation
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dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/http://linkinghub.elsevier.com/retrieve/pii/S1007570417303672
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.1016/j.cnsns.2017.10.013
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