Missing ordinal patterns in correlated noises

Recent research aiming at the distinction between deterministic or stochastic behavior in observational time series has looked into the properties of the "ordinal patterns" [C. Bandt, B. Pompe, Phys. Rev. Lett. 88 (2002) 174102]. In particular, new insight has been obtained considering the...

Descripción completa

Guardado en:
Detalles Bibliográficos
Autores principales: Carpi, L.C., Saco, P.M., Rosso, O.A.
Formato: JOUR
Materias:
Fluctuation phenomena
Noise
Noise and Brownian motion
Random processes
Time series analysis
Brownian motion
Correlated noise
Correlation structure
Decay rate
Fractional Brownian motion
Fractional Gaussian noise
One dimensional map
Ordinal pattern
Stochastic behavior
Stochastic process
White Gaussian Noise
Brownian movement
Decay (organic)
Gaussian noise (electronic)
Stochastic systems
Time and motion study
Time series
White noise
Acceso en línea:http://hdl.handle.net/20.500.12110/paper_03784371_v389_n10_p2020_Carpi
Aporte de:
Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA) de Universidad de Buenos Aires
id todo:paper_03784371_v389_n10_p2020_Carpi
record_format dspace
spelling todo:paper_03784371_v389_n10_p2020_Carpi2023-10-03T15:32:55Z Missing ordinal patterns in correlated noises Carpi, L.C. Saco, P.M. Rosso, O.A. Fluctuation phenomena Noise Noise and Brownian motion Random processes Time series analysis Brownian motion Correlated noise Correlation structure Decay rate Fluctuation phenomena Fractional Brownian motion Fractional Gaussian noise Noise Noise and Brownian motion One dimensional map Ordinal pattern Stochastic behavior Stochastic process White Gaussian Noise Brownian movement Decay (organic) Gaussian noise (electronic) Stochastic systems Time and motion study Time series White noise Time series analysis Recent research aiming at the distinction between deterministic or stochastic behavior in observational time series has looked into the properties of the "ordinal patterns" [C. Bandt, B. Pompe, Phys. Rev. Lett. 88 (2002) 174102]. In particular, new insight has been obtained considering the emergence of the so-called "forbidden ordinal patterns" [J.M. Amigó, S. Zambrano, M.A. F Sanjuán, Europhys. Lett. 79 (2007) 50001]. It was shown that deterministic one-dimensional maps always have forbidden ordinal patterns, in contrast with time series generated by an unconstrained stochastic process in which all the patterns appear with probability one. Techniques based on the comparison of this property in an observational time series and in white Gaussian noise were implemented. However, the comparison with correlated stochastic processes was not considered. In this paper we used the concept of "missing ordinal patterns" to study their decay rate as a function of the time series length in three stochastic processes with different degrees of correlation: fractional Brownian motion, fractional Gaussian noise and, noises with f- k power spectrum. We show that the decay rate of "missing ordinal patterns" in these processes depend on their correlation structures. We finally discuss the implications of the present results for the use of these properties as a tool for distinguishing deterministic from stochastic processes. © 2010 Elsevier B.V. All rights reserved. JOUR info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by/2.5/ar http://hdl.handle.net/20.500.12110/paper_03784371_v389_n10_p2020_Carpi
institution Universidad de Buenos Aires
institution_str I-28
repository_str R-134
collection Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA)
topic Fluctuation phenomena
Noise
Noise and Brownian motion
Random processes
Time series analysis
Brownian motion
Correlated noise
Correlation structure
Decay rate
Fluctuation phenomena
Fractional Brownian motion
Fractional Gaussian noise
Noise
Noise and Brownian motion
One dimensional map
Ordinal pattern
Stochastic behavior
Stochastic process
White Gaussian Noise
Brownian movement
Decay (organic)
Gaussian noise (electronic)
Stochastic systems
Time and motion study
Time series
White noise
Time series analysis
spellingShingle Fluctuation phenomena
Noise
Noise and Brownian motion
Random processes
Time series analysis
Brownian motion
Correlated noise
Correlation structure
Decay rate
Fluctuation phenomena
Fractional Brownian motion
Fractional Gaussian noise
Noise
Noise and Brownian motion
One dimensional map
Ordinal pattern
Stochastic behavior
Stochastic process
White Gaussian Noise
Brownian movement
Decay (organic)
Gaussian noise (electronic)
Stochastic systems
Time and motion study
Time series
White noise
Time series analysis
Carpi, L.C.
Saco, P.M.
Rosso, O.A.
Missing ordinal patterns in correlated noises
topic_facet Fluctuation phenomena
Noise
Noise and Brownian motion
Random processes
Time series analysis
Brownian motion
Correlated noise
Correlation structure
Decay rate
Fluctuation phenomena
Fractional Brownian motion
Fractional Gaussian noise
Noise
Noise and Brownian motion
One dimensional map
Ordinal pattern
Stochastic behavior
Stochastic process
White Gaussian Noise
Brownian movement
Decay (organic)
Gaussian noise (electronic)
Stochastic systems
Time and motion study
Time series
White noise
Time series analysis
description Recent research aiming at the distinction between deterministic or stochastic behavior in observational time series has looked into the properties of the "ordinal patterns" [C. Bandt, B. Pompe, Phys. Rev. Lett. 88 (2002) 174102]. In particular, new insight has been obtained considering the emergence of the so-called "forbidden ordinal patterns" [J.M. Amigó, S. Zambrano, M.A. F Sanjuán, Europhys. Lett. 79 (2007) 50001]. It was shown that deterministic one-dimensional maps always have forbidden ordinal patterns, in contrast with time series generated by an unconstrained stochastic process in which all the patterns appear with probability one. Techniques based on the comparison of this property in an observational time series and in white Gaussian noise were implemented. However, the comparison with correlated stochastic processes was not considered. In this paper we used the concept of "missing ordinal patterns" to study their decay rate as a function of the time series length in three stochastic processes with different degrees of correlation: fractional Brownian motion, fractional Gaussian noise and, noises with f- k power spectrum. We show that the decay rate of "missing ordinal patterns" in these processes depend on their correlation structures. We finally discuss the implications of the present results for the use of these properties as a tool for distinguishing deterministic from stochastic processes. © 2010 Elsevier B.V. All rights reserved.
format JOUR
author Carpi, L.C.
Saco, P.M.
Rosso, O.A.
author_facet Carpi, L.C.
Saco, P.M.
Rosso, O.A.
author_sort Carpi, L.C.
title Missing ordinal patterns in correlated noises
title_short Missing ordinal patterns in correlated noises
title_full Missing ordinal patterns in correlated noises
title_fullStr Missing ordinal patterns in correlated noises
title_full_unstemmed Missing ordinal patterns in correlated noises
title_sort missing ordinal patterns in correlated noises
url http://hdl.handle.net/20.500.12110/paper_03784371_v389_n10_p2020_Carpi
work_keys_str_mv AT carpilc missingordinalpatternsincorrelatednoises
AT sacopm missingordinalpatternsincorrelatednoises
AT rossooa missingordinalpatternsincorrelatednoises
_version_ 1782029896260780032

Ejemplares similares