A comparison of waveform fractal dimension algorithms

By R. Esteller, George J. Vachtsevanos, J. Echauz, Brian Litt. 2001

488 citations recorded by the source corpus.

How researchers see this paper

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Classifying depression patients and normal subjects using machine learning techniques (2011, methodology): “Higuchi iguchi is an algorithm for measuring fractal dimension of ime series and is used to quantify complexity and selfimilarity of signal [13].”
An open-source, high-performance tool for automated sleep staging (2021, background): “…are calculated, including the number of zero-crossings, the Hjorth parameters of mobility and complexity ( Hjorth, 1970 ), the permutation entropy ( Bandt and Pompe, 2002 ; Lajnef et al., 2015 ), and the fractal dimension ( Esteller et al., 2001 ; Higuchi, 1988 ; Petrosian, 1995 ) of the signal.”
A review of change point detection methods (2018, background): “For instance, it has been applied on biological signals [28, 47, 63, 73, 131], on network data [94, 97], on speech time series [1, 42, 63] and on financial time series [22, 34, 78].”
Selective review of offline change point detection methods (2020, unknown): “Win has been applied in numerous contexts: for instance, on biological signals [11, 114–117], on network data [28, 29], on speech time series [10, 11, 118] and on financial time series [3, 119, 120].”