RT journal article
T1 Crossover detection based on variances of slope differences for multi-fractal detrended fluctuation analysis (MF-DFA)
A1 Moreno Pulido, Soledad
A1 Torre Macías, Juan Carlos de la
A1 Ruiz Villalobos, Patricia
A1 Pavón Domínguez, Pablo
A2 Ingeniería Informática
A2 Ingeniería Mecánica y Diseño Industrial
A2 Matemáticas
K1 MF-DFA
K1 Automatic detection of Crossover
K1 CDV-A
K1 Detrended
K1 Long-range correlations
K1 Multi-fractal
AB Multi-fractal detrended fluctuation analysis (MF-DFA) describes long-range correlations across scales in time series in terms of the linear fittings of the fluctuation functions  for every moment q considered. It is relatively common to find time scales, also called crossovers, where different linearities are found at each side of the , leading to different (multi-)fractal properties. Generally, crossovers are manually identified by experts, subject then to their skills and possible bias. In this work, a novel methodology based on the variances of the slope differences (CDV-A) is proposed to automatically detect crossovers. A set of synthetic fluctuation functions with different mono-fractal and multi-fractal features, different noise levels and known crossovers is generated to assess the CDV-A. Moreover, the proposed methodology is also applied to state of the art fluctuation functions in order to compare the proposed manual and automated locations of the crossovers. Results show the proposed methodology is highly accurate, specially in low noise synthetic fluctuation functions and in most of the real cases.
PB Springer
SN 1573-269X
YR 2024
FD 2024-11-20
LK http://hdl.handle.net/10498/35448
UL http://hdl.handle.net/10498/35448
LA eng
DS Repositorio Institucional de la Universidad de Cádiz
RD 06-nov-2026