Artículos de revistas
Quantifying long-range correlations with a multiscale ordinal pattern approach
Fecha
2016-03Registro en:
Olivares Zamora, Felipe Esteban; Zunino, Luciano José; Rosso, Osvaldo Aníbal; Quantifying long-range correlations with a multiscale ordinal pattern approach; Elsevier Science; Physica A: Statistical Mechanics and its Applications; 445; 3-2016; 283-294
0378-4371
CONICET Digital
CONICET
Autor
Olivares Zamora, Felipe Esteban
Zunino, Luciano José
Rosso, Osvaldo Aníbal
Resumen
In this paper we use the ordinal patterns probabilities associated with fractional Brownian motions for estimating the Hurst exponent of artificially generated and experimentally measured data. Numerical analysis show a reliable estimation of this scaling parameter, even when data with low resolution are analysed. Robustness to observational noise is also obtained. Several experimental applications allow us to confirm the practical utility of the proposed approach. We contrast results obtained by implementing this multiscale symbolic tool with those obtained from the classical detrended fluctuation analysis.