Wavelet-based discrimination of isolated singularities masquerading as multifractals in detrended fluctuation analyses

Autores
Oswiecimka, Pawel; Drozdz, Stanislaw; Frasca, Mattia; Gebarowski, Robert; Yoshimura, Natsue; Zunino, Luciano José; Minati, Ludovico
Año de publicación
2020
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
The robustness of two widespread multifractal analysis methods, one based on detrended fluctuation analysis and one on wavelet leaders, is discussed in the context of time-series containing non-uniform structures with only isolated singularities. Signals generated by simulated and experimentally-realized chaos generators, together with synthetic data addressing particular aspects, are taken into consideration. The results reveal essential limitations affecting the ability of both methods to correctly infer the non-multifractal nature of signals devoid of a cascade-like hierarchy of singularities. Namely, signals harboring only isolated singularities are found to artefactually give rise to broad multifractal spectra, resembling those expected in the presence of a well-developed underlying multifractal structure. Hence, there is a real risk of incorrectly inferring multifractality due to isolated singularities. The careful consideration of local scaling properties and the distribution of Hölder exponent obtained, for example, through wavelet analysis, is indispensable for rigorously assessing the presence or absence of multifractality.
Fil: Oswiecimka, Pawel. Polish Academy of Sciences; Argentina
Fil: Drozdz, Stanislaw. Cracow University of Technology. Faculty of Materials Engineering and Physics; Polonia
Fil: Frasca, Mattia. University of Catania. Department of Electrical Electronic and Computer Engineering; Italia
Fil: Gebarowski, Robert. Cracow University of Technology. Faculty of Materials Engineering and Physics; Polonia
Fil: Yoshimura, Natsue. Tokyo Institute of Technology. Institute of Innovative Research. FIRST; Japón
Fil: Zunino, Luciano José. Universidad Nacional de La Plata. Facultad de Ingeniería. Departamento de Ciencias Básicas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Centro de Investigaciones Ópticas. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas. Centro de Investigaciones Ópticas. Universidad Nacional de La Plata. Centro de Investigaciones Ópticas; Argentina
Fil: Minati, Ludovico. Universita degli Studi di Trento; Italia. Polish Academy of Sciences; Argentina
Materia
CHAOTIC OSCILLATOR
COMPLEXITY
DYNAMICAL SYSTEM
HÖLDER EXPONENTS
MULTIFRACTAL ANALYSIS
MULTIFRACTAL SPECTRUM
SINGULARITY
TIME-SERIES ANALYSIS
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/144084
Acceder
id CONICETDig_4b39ef83d18469b49708a1d152f80d77
oai_identifier_str oai:ri.conicet.gov.ar:11336/144084
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Wavelet-based discrimination of isolated singularities masquerading as multifractals in detrended fluctuation analysesOswiecimka, PawelDrozdz, StanislawFrasca, MattiaGebarowski, RobertYoshimura, NatsueZunino, Luciano JoséMinati, LudovicoCHAOTIC OSCILLATORCOMPLEXITYDYNAMICAL SYSTEMHÖLDER EXPONENTSMULTIFRACTAL ANALYSISMULTIFRACTAL SPECTRUMSINGULARITYTIME-SERIES ANALYSIShttps://purl.org/becyt/ford/1.3https://purl.org/becyt/ford/1The robustness of two widespread multifractal analysis methods, one based on detrended fluctuation analysis and one on wavelet leaders, is discussed in the context of time-series containing non-uniform structures with only isolated singularities. Signals generated by simulated and experimentally-realized chaos generators, together with synthetic data addressing particular aspects, are taken into consideration. The results reveal essential limitations affecting the ability of both methods to correctly infer the non-multifractal nature of signals devoid of a cascade-like hierarchy of singularities. Namely, signals harboring only isolated singularities are found to artefactually give rise to broad multifractal spectra, resembling those expected in the presence of a well-developed underlying multifractal structure. Hence, there is a real risk of incorrectly inferring multifractality due to isolated singularities. The careful consideration of local scaling properties and the distribution of Hölder exponent obtained, for example, through wavelet analysis, is indispensable for rigorously assessing the presence or absence of multifractality.Fil: Oswiecimka, Pawel. Polish Academy of Sciences; ArgentinaFil: Drozdz, Stanislaw. Cracow University of Technology. Faculty of Materials Engineering and Physics; PoloniaFil: Frasca, Mattia. University of Catania. Department of Electrical Electronic and Computer Engineering; ItaliaFil: Gebarowski, Robert. Cracow University of Technology. Faculty of Materials Engineering and Physics; PoloniaFil: Yoshimura, Natsue. Tokyo Institute of Technology. Institute of Innovative Research. FIRST; JapónFil: Zunino, Luciano José. Universidad Nacional de La Plata. Facultad de Ingeniería. Departamento de Ciencias Básicas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Centro de Investigaciones Ópticas. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas. Centro de Investigaciones Ópticas. Universidad Nacional de La Plata. Centro de Investigaciones Ópticas; ArgentinaFil: Minati, Ludovico. Universita degli Studi di Trento; Italia. Polish Academy of Sciences; ArgentinaSpringer2020-04-03info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/144084Oswiecimka, Pawel; Drozdz, Stanislaw; Frasca, Mattia; Gebarowski, Robert; Yoshimura, Natsue; et al.; Wavelet-based discrimination of isolated singularities masquerading as multifractals in detrended fluctuation analyses; Springer; Nonlinear Dynamics; 100; 2; 03-4-2020; 1689-17040924-090XCONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/http://link.springer.com/10.1007/s11071-020-05581-yinfo:eu-repo/semantics/altIdentifier/doi/10.1007/s11071-020-05581-yinfo:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-11-26T09:05:27Zoai:ri.conicet.gov.ar:11336/144084instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-11-26 09:05:27.294CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Wavelet-based discrimination of isolated singularities masquerading as multifractals in detrended fluctuation analyses
title Wavelet-based discrimination of isolated singularities masquerading as multifractals in detrended fluctuation analyses
spellingShingle Wavelet-based discrimination of isolated singularities masquerading as multifractals in detrended fluctuation analyses
Oswiecimka, Pawel
CHAOTIC OSCILLATOR
COMPLEXITY
DYNAMICAL SYSTEM
HÖLDER EXPONENTS
MULTIFRACTAL ANALYSIS
MULTIFRACTAL SPECTRUM
SINGULARITY
TIME-SERIES ANALYSIS
title_short Wavelet-based discrimination of isolated singularities masquerading as multifractals in detrended fluctuation analyses
title_full Wavelet-based discrimination of isolated singularities masquerading as multifractals in detrended fluctuation analyses
title_fullStr Wavelet-based discrimination of isolated singularities masquerading as multifractals in detrended fluctuation analyses
title_full_unstemmed Wavelet-based discrimination of isolated singularities masquerading as multifractals in detrended fluctuation analyses
title_sort Wavelet-based discrimination of isolated singularities masquerading as multifractals in detrended fluctuation analyses
dc.creator.none.fl_str_mv Oswiecimka, Pawel
Drozdz, Stanislaw
Frasca, Mattia
Gebarowski, Robert
Yoshimura, Natsue
Zunino, Luciano José
Minati, Ludovico
author Oswiecimka, Pawel
author_facet Oswiecimka, Pawel
Drozdz, Stanislaw
Frasca, Mattia
Gebarowski, Robert
Yoshimura, Natsue
Zunino, Luciano José
Minati, Ludovico
author_role author
author2 Drozdz, Stanislaw
Frasca, Mattia
Gebarowski, Robert
Yoshimura, Natsue
Zunino, Luciano José
Minati, Ludovico
author2_role author
author
author
author
author
author
dc.subject.none.fl_str_mv CHAOTIC OSCILLATOR
COMPLEXITY
DYNAMICAL SYSTEM
HÖLDER EXPONENTS
MULTIFRACTAL ANALYSIS
MULTIFRACTAL SPECTRUM
SINGULARITY
TIME-SERIES ANALYSIS
topic CHAOTIC OSCILLATOR
COMPLEXITY
DYNAMICAL SYSTEM
HÖLDER EXPONENTS
MULTIFRACTAL ANALYSIS
MULTIFRACTAL SPECTRUM
SINGULARITY
TIME-SERIES ANALYSIS
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.3
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv The robustness of two widespread multifractal analysis methods, one based on detrended fluctuation analysis and one on wavelet leaders, is discussed in the context of time-series containing non-uniform structures with only isolated singularities. Signals generated by simulated and experimentally-realized chaos generators, together with synthetic data addressing particular aspects, are taken into consideration. The results reveal essential limitations affecting the ability of both methods to correctly infer the non-multifractal nature of signals devoid of a cascade-like hierarchy of singularities. Namely, signals harboring only isolated singularities are found to artefactually give rise to broad multifractal spectra, resembling those expected in the presence of a well-developed underlying multifractal structure. Hence, there is a real risk of incorrectly inferring multifractality due to isolated singularities. The careful consideration of local scaling properties and the distribution of Hölder exponent obtained, for example, through wavelet analysis, is indispensable for rigorously assessing the presence or absence of multifractality.
Fil: Oswiecimka, Pawel. Polish Academy of Sciences; Argentina
Fil: Drozdz, Stanislaw. Cracow University of Technology. Faculty of Materials Engineering and Physics; Polonia
Fil: Frasca, Mattia. University of Catania. Department of Electrical Electronic and Computer Engineering; Italia
Fil: Gebarowski, Robert. Cracow University of Technology. Faculty of Materials Engineering and Physics; Polonia
Fil: Yoshimura, Natsue. Tokyo Institute of Technology. Institute of Innovative Research. FIRST; Japón
Fil: Zunino, Luciano José. Universidad Nacional de La Plata. Facultad de Ingeniería. Departamento de Ciencias Básicas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Centro de Investigaciones Ópticas. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas. Centro de Investigaciones Ópticas. Universidad Nacional de La Plata. Centro de Investigaciones Ópticas; Argentina
Fil: Minati, Ludovico. Universita degli Studi di Trento; Italia. Polish Academy of Sciences; Argentina
description The robustness of two widespread multifractal analysis methods, one based on detrended fluctuation analysis and one on wavelet leaders, is discussed in the context of time-series containing non-uniform structures with only isolated singularities. Signals generated by simulated and experimentally-realized chaos generators, together with synthetic data addressing particular aspects, are taken into consideration. The results reveal essential limitations affecting the ability of both methods to correctly infer the non-multifractal nature of signals devoid of a cascade-like hierarchy of singularities. Namely, signals harboring only isolated singularities are found to artefactually give rise to broad multifractal spectra, resembling those expected in the presence of a well-developed underlying multifractal structure. Hence, there is a real risk of incorrectly inferring multifractality due to isolated singularities. The careful consideration of local scaling properties and the distribution of Hölder exponent obtained, for example, through wavelet analysis, is indispensable for rigorously assessing the presence or absence of multifractality.
publishDate 2020
dc.date.none.fl_str_mv 2020-04-03
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/144084
Oswiecimka, Pawel; Drozdz, Stanislaw; Frasca, Mattia; Gebarowski, Robert; Yoshimura, Natsue; et al.; Wavelet-based discrimination of isolated singularities masquerading as multifractals in detrended fluctuation analyses; Springer; Nonlinear Dynamics; 100; 2; 03-4-2020; 1689-1704
0924-090X
CONICET Digital
CONICET
url http://hdl.handle.net/11336/144084
identifier_str_mv Oswiecimka, Pawel; Drozdz, Stanislaw; Frasca, Mattia; Gebarowski, Robert; Yoshimura, Natsue; et al.; Wavelet-based discrimination of isolated singularities masquerading as multifractals in detrended fluctuation analyses; Springer; Nonlinear Dynamics; 100; 2; 03-4-2020; 1689-1704
0924-090X
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/http://link.springer.com/10.1007/s11071-020-05581-y
info:eu-repo/semantics/altIdentifier/doi/10.1007/s11071-020-05581-y
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Springer
publisher.none.fl_str_mv Springer
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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score 13.011256

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