Permutation entropy and its main biomedical and econophysics applications: a review
Entropy is a powerful tool for the analysis of time series, as it allows describing the
probability distributions of the possible state of a system, and therefore the information …
probability distributions of the possible state of a system, and therefore the information …
Practical considerations of permutation entropy: A tutorial review
M Riedl, A Müller, N Wessel - The European Physical Journal Special …, 2013 - Springer
More than ten years ago Bandt and Pompe introduced a new measure to quantify
complexity in measured time series. During these ten years, this measure has been modified …
complexity in measured time series. During these ten years, this measure has been modified …
Dispersion entropy: A measure for time-series analysis
M Rostaghi, H Azami - IEEE Signal Processing Letters, 2016 - ieeexplore.ieee.org
One of the most powerful tools to assess the dynamical characteristics of time series is
entropy. Sample entropy (SE), though powerful, is not fast enough, especially for long …
entropy. Sample entropy (SE), though powerful, is not fast enough, especially for long …
Distinguishing noise from chaos
Chaotic systems share with stochastic processes several properties that make them almost
undistinguishable. In this communication we introduce a representation space, to be called …
undistinguishable. In this communication we introduce a representation space, to be called …
Amplitude-and fluctuation-based dispersion entropy
H Azami, J Escudero - Entropy, 2018 - mdpi.com
Dispersion entropy (DispEn) is a recently introduced entropy metric to quantify the
uncertainty of time series. It is fast and, so far, it has demonstrated very good performance in …
uncertainty of time series. It is fast and, so far, it has demonstrated very good performance in …
Improved multiscale permutation entropy for biomedical signal analysis: Interpretation and application to electroencephalogram recordings
H Azami, J Escudero - Biomedical Signal Processing and Control, 2016 - Elsevier
Permutation entropy (PE) is a well-known and fast method extensively used in many
physiological signal processing applications to measure the irregularity of time series …
physiological signal processing applications to measure the irregularity of time series …
Forbidden patterns, permutation entropy and stock market inefficiency
In this paper we introduce two new quantifiers for the stock market inefficiency: the number
of forbidden patterns and the normalized permutation entropy. They are model-independent …
of forbidden patterns and the normalized permutation entropy. They are model-independent …
Automated emotion identification using Fourier–Bessel domain-based entropies
Human dependence on computers is increasing day by day; thus, human interaction with
computers must be more dynamic and contextual rather than static or generalized. The …
computers must be more dynamic and contextual rather than static or generalized. The …
Amplitude-aware permutation entropy: Illustration in spike detection and signal segmentation
H Azami, J Escudero - Computer methods and programs in biomedicine, 2016 - Elsevier
Background and objective Signal segmentation and spike detection are two important
biomedical signal processing applications. Often, non-stationary signals must be segmented …
biomedical signal processing applications. Often, non-stationary signals must be segmented …
Complexity-entropy causality plane: A useful approach to quantify the stock market inefficiency
The complexity-entropy causality plane has been recently introduced as a powerful tool for
discriminating Gaussian from non-Gaussian process and different degrees of correlations …
discriminating Gaussian from non-Gaussian process and different degrees of correlations …