Permutation entropy based time series analysis: equalities in the input signal can lead to false conclusions

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"A symbolic encoding scheme, based on the ordinal relation between the amplitude of neighboring values of a given data sequence, should be implemented before estimating the permutation entropy. Consequently, equalities in the analyzed signal, i.e. repeated equal values, deserve special attentio...

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Detalles Bibliográficos
Autores principales: Zunino, Luciano, Olivares, Felipe, Scholkmann, Felix, Rosso, Osvaldo A.
Formato: Artículos de Publicaciones Periódicas acceptedVersion
Lenguaje:Inglés
Publicado: 2019
Materias:
ANALISIS DE SERIES DE TIEMPO
ENTROPIA
ANALISIS DE FALLAS
DISEÑO EXPERIMENTAL
Acceso en línea:http://ri.itba.edu.ar/handle/123456789/1766
Aporte de:
Repositorio Institucional Instituto Tecnológico de Buenos Aires (ITBA) de Instituto Tecnológico de Buenos Aires (ITBA)
id I32-R138-123456789-1766
record_format dspace
spelling I32-R138-123456789-17662022-12-07T13:06:33Z Permutation entropy based time series analysis: equalities in the input signal can lead to false conclusions Zunino, Luciano Olivares, Felipe Scholkmann, Felix Rosso, Osvaldo A. ANALISIS DE SERIES DE TIEMPO ENTROPIA ANALISIS DE FALLAS DISEÑO EXPERIMENTAL "A symbolic encoding scheme, based on the ordinal relation between the amplitude of neighboring values of a given data sequence, should be implemented before estimating the permutation entropy. Consequently, equalities in the analyzed signal, i.e. repeated equal values, deserve special attention and treatment. In this work, we carefully study the effect that the presence of equalities has on permutation entropy estimated values when these ties are symbolized, as it is commonly done, according to their order of appearance. On the one hand, the analysis of computer-generated time series is initially developed to understand the incidence of repeated values on permutation entropy estimations in controlled scenarios. The presence of temporal correlations is erroneously concluded when true pseudorandom time series with low amplitude resolutions are considered. On the other hand, the analysis of real-world data is included to illustrate how the presence of a significant number of equal values can give rise to false conclusions regarding the underlying temporal structures in practical contexts." 2019-09-25T19:22:45Z 2019-09-25T19:22:45Z 2017-06 Artículos de Publicaciones Periódicas info:eu-repo/semantics/acceptedVersion 0375-9601 http://ri.itba.edu.ar/handle/123456789/1766 en info:eu-repo/semantics/altIdentifier/doi/10.1016/j.physleta.2017.03.052 info:eu-repo/grantAgreement/CONICET/AR. Cuidad Autónoma de Buenos Aires application/pdf application/pdf
institution Instituto Tecnológico de Buenos Aires (ITBA)
institution_str I-32
repository_str R-138
collection Repositorio Institucional Instituto Tecnológico de Buenos Aires (ITBA)
language Inglés
topic ANALISIS DE SERIES DE TIEMPO
ENTROPIA
ANALISIS DE FALLAS
DISEÑO EXPERIMENTAL
spellingShingle ANALISIS DE SERIES DE TIEMPO
ENTROPIA
ANALISIS DE FALLAS
DISEÑO EXPERIMENTAL
Zunino, Luciano
Olivares, Felipe
Scholkmann, Felix
Rosso, Osvaldo A.
Permutation entropy based time series analysis: equalities in the input signal can lead to false conclusions
topic_facet ANALISIS DE SERIES DE TIEMPO
ENTROPIA
ANALISIS DE FALLAS
DISEÑO EXPERIMENTAL
description "A symbolic encoding scheme, based on the ordinal relation between the amplitude of neighboring values of a given data sequence, should be implemented before estimating the permutation entropy. Consequently, equalities in the analyzed signal, i.e. repeated equal values, deserve special attention and treatment. In this work, we carefully study the effect that the presence of equalities has on permutation entropy estimated values when these ties are symbolized, as it is commonly done, according to their order of appearance. On the one hand, the analysis of computer-generated time series is initially developed to understand the incidence of repeated values on permutation entropy estimations in controlled scenarios. The presence of temporal correlations is erroneously concluded when true pseudorandom time series with low amplitude resolutions are considered. On the other hand, the analysis of real-world data is included to illustrate how the presence of a significant number of equal values can give rise to false conclusions regarding the underlying temporal structures in practical contexts."
format Artículos de Publicaciones Periódicas
acceptedVersion
author Zunino, Luciano
Olivares, Felipe
Scholkmann, Felix
Rosso, Osvaldo A.
author_facet Zunino, Luciano
Olivares, Felipe
Scholkmann, Felix
Rosso, Osvaldo A.
author_sort Zunino, Luciano
title Permutation entropy based time series analysis: equalities in the input signal can lead to false conclusions
title_short Permutation entropy based time series analysis: equalities in the input signal can lead to false conclusions
title_full Permutation entropy based time series analysis: equalities in the input signal can lead to false conclusions
title_fullStr Permutation entropy based time series analysis: equalities in the input signal can lead to false conclusions
title_full_unstemmed Permutation entropy based time series analysis: equalities in the input signal can lead to false conclusions
title_sort permutation entropy based time series analysis: equalities in the input signal can lead to false conclusions
publishDate 2019
url http://ri.itba.edu.ar/handle/123456789/1766
work_keys_str_mv AT zuninoluciano permutationentropybasedtimeseriesanalysisequalitiesintheinputsignalcanleadtofalseconclusions
AT olivaresfelipe permutationentropybasedtimeseriesanalysisequalitiesintheinputsignalcanleadtofalseconclusions
AT scholkmannfelix permutationentropybasedtimeseriesanalysisequalitiesintheinputsignalcanleadtofalseconclusions
AT rossoosvaldoa permutationentropybasedtimeseriesanalysisequalitiesintheinputsignalcanleadtofalseconclusions
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