Modern financial markets are characterized by a rapid flow of information, a vast number of
participants having diversified investment horizons, and multiple feedback mechanisms …

Multifractality is ubiquitously observed in complex natural and socioeconomic systems.
Multifractal analysis provides powerful tools to understand the complex nonlinear nature of …

The paradigm of deterministic chaos has influenced thinking in many fields of science.
Chaotic systems show rich and surprising mathematical structures. In the applied sciences …

We develop a method for the multifractal characterization of nonstationary time series, which
is based on a generalization of the detrended fluctuation analysis (DFA). We relate our …

Driving fatigue seriously threatens traffic safety. In our work, the multifractal detrended
fluctuation analysis (MF-DFA) method is proposed to detect driver fatigue caused by driving …

Fractal structures are found in biomedical time series from a wide range of physiological
phenomena. The multifractal spectrum identifies the deviations in fractal structure within time …

Detrended fluctuation analysis (DFA) is a scaling analysis method used to estimate long-
range power-law correlation exponents in noisy signals. Many noisy signals in real systems …

Detrended fluctuation analysis (DFA) is a scaling analysis method used to quantify long-
range power-law correlations in signals. Many physical and biological signals are “noisy,” …

Global warming, extreme climate events, earthquakes and their accompanying
socioeconomic disasters pose significant risks to humanity. Yet due to the nonlinear …

Recent years of research have shown that the complex temporal structure of ongoing
oscillations is scale-free and characterized by long-range temporal correlations. Detrended …