Introduction to multifractal detrended fluctuation analysis in matlab. [PDF]
Front Physiol, 2012 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 periods with large and small fluctuations.
Ihlen EA.
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Multifractal detrended fluctuation analysis of nonstationary time series [PDF]
Physica A: Statistical Mechanics and its Applications, 2002 We develop a method for the multifractal characterization of nonstationary time series, which is based on a generalization of the detrended fluctuation analysis (DFA).
Alados +50 more
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Multifractal Detrended Fluctuation Analysis of Human gait Diseases [PDF]
Frontiers in Physiology, 2013 IIn this paper multifractal detrended fluctuation analysis is used to study the human gait time series for normal and diseased sets. It is observed that long range correlation is primarily responsible for the origin of multifractality.
Srimonti eDutta +2 more
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Characterizing stroke-induced changes in the variability of lower limb kinematics using multifractal detrended fluctuation analysis [PDF]
Frontiers in Neurology, 2022 Movement variability reflects the adaptation of the neuromuscular control system to internal or external perturbations, but its relationship to stroke-induced injury is still unclear.
Pan Xu +6 more
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EEG based cognitive task classification using multifractal detrended fluctuation analysis. [PDF]
Cogn Neurodyn, 2021 Locating cognitive task states by measuring changes in electrocortical activity due to various attentional and sensory-motor changes, has been in research interest since last few decades. In this paper, different cognitive states while performing various attentional and visuo-motor coordination tasks, are classified using electroencephalogram (EEG ...
Gaurav G, Anand RS, Kumar V.
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MFDFA: Efficient multifractal detrended fluctuation analysis in python [PDF]
Computer Physics Communications, 2021 Multifractal detrended fluctuation analysis (MFDFA) has become a central method to characterise the variability and uncertainty in empiric time series.
Leonardo Rydin Gorjão +3 more
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Multifractal Flexibly Detrended Fluctuation Analysis [PDF]
Acta Physica Polonica B, 2015 Multifractal time series analysis is a approach that shows the possible complexity of the system. Nowadays, one of the most popular and the best methods for determining multifractal characteristics is Multifractal Detrended Fluctuation Analysis (MFDFA ...
Rak, Rafal, Zięba, Pawel
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Wavelet versus Detrended Fluctuation Analysis of multifractal structures [PDF]
Physical Review E, 2006 We perform a comparative study of applicability of the Multifractal Detrended Fluctuation Analysis (MFDFA) and the Wavelet Transform Modulus Maxima (WTMM) method in proper detecting of mono- and multifractal character of data. We quantify the performance
B. B. Mandelbrot +6 more
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Multifractal detrended fluctuation analysis of human EEG: preliminary investigation and comparison with the wavelet transform modulus maxima technique. [PDF]
PLoS ONE, 2013 Recently, many lines of investigation in neuroscience and statistical physics have converged to raise the hypothesis that the underlying pattern of neuronal activation which results in electroencephalography (EEG) signals is nonlinear, with self-affine ...
Todd Zorick, Mark A Mandelkern
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Two-dimensional multifractal detrended fluctuation analysis for plant identification. [PDF]
Plant Methods, 2015 In this paper, a novel method is proposed to identify plant species by using the two- dimensional multifractal detrended fluctuation analysis (2D MF-DFA). Our method involves calculating a set of multifractal parameters that characterize the texture features of each plant leaf image.
Wang F, Liao DW, Li JW, Liao GP.
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