Permutation-information-theory approach to unveil delay dynamics from time-series analysis

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In this paper an approach to identify delay phenomena from time series is developed. We show that it is possible to perform a reliable time delay identification by using quantifiers derived from information theory, more precisely, permutation entropy and permutation statistical complexity. These qua...

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Autores principales:	Zunino, L., Soriano, M.C., Fischer, I., Rosso, O.A., Mirasso, C.R.
Formato:	JOUR
Materias:	Characteristic time Delay dynamics Dynamical noise Feedback rates High nonlinearity Mackey-Glass equations Noise environments Numerical data Permutation approach Permutation entropy Statistical complexity Time delay identification Time-delay systems Equipment testing Harmonic analysis Information theory Time delay Time series Time series analysis
Acceso en línea:	http://hdl.handle.net/20.500.12110/paper_15393755_v82_n4_p_Zunino
Aporte de:	Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA) de Universidad de Buenos Aires

id	todo:paper_15393755_v82_n4_p_Zunino
record_format	dspace
spelling	todo:paper_15393755_v82_n4_p_Zunino2023-10-03T16:22:34Z Permutation-information-theory approach to unveil delay dynamics from time-series analysis Zunino, L. Soriano, M.C. Fischer, I. Rosso, O.A. Mirasso, C.R. Characteristic time Delay dynamics Dynamical noise Feedback rates High nonlinearity Mackey-Glass equations Noise environments Numerical data Permutation approach Permutation entropy Statistical complexity Time delay identification Time-delay systems Equipment testing Harmonic analysis Information theory Time delay Time series Time series analysis In this paper an approach to identify delay phenomena from time series is developed. We show that it is possible to perform a reliable time delay identification by using quantifiers derived from information theory, more precisely, permutation entropy and permutation statistical complexity. These quantifiers show clear extrema when the embedding delay τ of the symbolic reconstruction matches the characteristic time delay τS of the system. Numerical data originating from a time delay system based on the well-known Mackey-Glass equations operating in the chaotic regime were used as test beds. We show that our method is straightforward to apply and robust to additive observational and dynamical noise. Moreover, we find that the identification of the time delay is even more efficient in a noise environment. Our permutation approach is also able to recover the time delay in systems with low feedback rate or high nonlinearity. © 2010 The American Physical Society. JOUR info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by/2.5/ar http://hdl.handle.net/20.500.12110/paper_15393755_v82_n4_p_Zunino
institution	Universidad de Buenos Aires
institution_str	I-28
repository_str	R-134
collection	Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA)
topic	Characteristic time Delay dynamics Dynamical noise Feedback rates High nonlinearity Mackey-Glass equations Noise environments Numerical data Permutation approach Permutation entropy Statistical complexity Time delay identification Time-delay systems Equipment testing Harmonic analysis Information theory Time delay Time series Time series analysis
spellingShingle	Characteristic time Delay dynamics Dynamical noise Feedback rates High nonlinearity Mackey-Glass equations Noise environments Numerical data Permutation approach Permutation entropy Statistical complexity Time delay identification Time-delay systems Equipment testing Harmonic analysis Information theory Time delay Time series Time series analysis Zunino, L. Soriano, M.C. Fischer, I. Rosso, O.A. Mirasso, C.R. Permutation-information-theory approach to unveil delay dynamics from time-series analysis
topic_facet	Characteristic time Delay dynamics Dynamical noise Feedback rates High nonlinearity Mackey-Glass equations Noise environments Numerical data Permutation approach Permutation entropy Statistical complexity Time delay identification Time-delay systems Equipment testing Harmonic analysis Information theory Time delay Time series Time series analysis
description	In this paper an approach to identify delay phenomena from time series is developed. We show that it is possible to perform a reliable time delay identification by using quantifiers derived from information theory, more precisely, permutation entropy and permutation statistical complexity. These quantifiers show clear extrema when the embedding delay τ of the symbolic reconstruction matches the characteristic time delay τS of the system. Numerical data originating from a time delay system based on the well-known Mackey-Glass equations operating in the chaotic regime were used as test beds. We show that our method is straightforward to apply and robust to additive observational and dynamical noise. Moreover, we find that the identification of the time delay is even more efficient in a noise environment. Our permutation approach is also able to recover the time delay in systems with low feedback rate or high nonlinearity. © 2010 The American Physical Society.
format	JOUR
author	Zunino, L. Soriano, M.C. Fischer, I. Rosso, O.A. Mirasso, C.R.
author_facet	Zunino, L. Soriano, M.C. Fischer, I. Rosso, O.A. Mirasso, C.R.
author_sort	Zunino, L.
title	Permutation-information-theory approach to unveil delay dynamics from time-series analysis
title_short	Permutation-information-theory approach to unveil delay dynamics from time-series analysis
title_full	Permutation-information-theory approach to unveil delay dynamics from time-series analysis
title_fullStr	Permutation-information-theory approach to unveil delay dynamics from time-series analysis
title_full_unstemmed	Permutation-information-theory approach to unveil delay dynamics from time-series analysis
title_sort	permutation-information-theory approach to unveil delay dynamics from time-series analysis
url	http://hdl.handle.net/20.500.12110/paper_15393755_v82_n4_p_Zunino
work_keys_str_mv	AT zuninol permutationinformationtheoryapproachtounveildelaydynamicsfromtimeseriesanalysis AT sorianomc permutationinformationtheoryapproachtounveildelaydynamicsfromtimeseriesanalysis AT fischeri permutationinformationtheoryapproachtounveildelaydynamicsfromtimeseriesanalysis AT rossooa permutationinformationtheoryapproachtounveildelaydynamicsfromtimeseriesanalysis AT mirassocr permutationinformationtheoryapproachtounveildelaydynamicsfromtimeseriesanalysis
_version_	1807321559145119744

Permutation-information-theory approach to unveil delay dynamics from time-series analysis

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