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Refined Composite Multiscale Permutation Entropy to Overcome Multiscale Permutation Entropy Length Dependence [PDF]

IEEE Signal Processing Letters, 2015
Multiscale permutation entropy (MPE) has recently been proposed to evaluate complexity of time series. MPE has numerous advantages over other multiscale complexity measures, such as its simplicity, robustness to noise and its low computational cost.
Anne Humeau-Heurtier, Chiu-Wen Wu, Shuen-De Wu   +2 more
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Multiscale Permutation Entropy Analysis of Electrocardiogram

Physica A: Statistical Mechanics and Its Applications, 2017
Abstract To make a comprehensive nonlinear analysis to ECG, multiscale permutation entropy (MPE) was applied to ECG characteristics extraction to make a comprehensive nonlinear analysis of ECG. Three kinds of ECG from PhysioNet database, congestive heart failure (CHF) patients, healthy young and elderly subjects, are applied in this paper.
Tiebing Liu, Wenpo Yao, Min Wu, Zhaorong Shi, Jun Wang, Xinbao Ning   +5 more
exaly   +2 more sources

Multiscale dynamics under the lens of permutation entropy

Physica A: Statistical Mechanics and its Applications, 2020
Abstract In this paper, we characterize multi-scaling dynamics by estimating the permutation entropy at different time lags. Numerical simulations generated from fractional Brownian motion were used to illustrate how this multiscale symbolic tool behaves at the crossovers between different scaling. Experimental applications were also analyzed to show
Olivares Zamora, Felipe Esteban, Zunino, Luciano José   +1 more
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Financial Time Series Analysis Based on Fractional and Multiscale Permutation Entropy

Communications in Nonlinear Science and Numerical Simulation, 2019
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Pengjian Shang
exaly   +2 more sources

Dynamic Characteristics of Absence EEG Recordings With Multiscale Permutation Entropy Analysis

Epilepsy Research, 2013
Understanding the transition of brain activities towards an absence seizure, called pre-epileptic seizure, is a challenge. In this study, multiscale permutation entropy (MPE) is proposed to describe dynamical characteristics of electroencephalograph (EEG) recordings on different absence seizure states.
Gaoxiang Ouyang, Xiaoli Li
exaly   +3 more sources

Weighted Multiscale Rényi Permutation Entropy of Nonlinear Time Series

Physica A: Statistical Mechanics and Its Applications, 2018
Abstract In this paper, based on Renyi permutation entropy (RPE), which has been recently suggested as a relative measure of complexity in nonlinear systems, we propose multiscale Renyi permutation entropy (MRPE) and weighted multiscale Renyi permutation entropy (WMRPE) to quantify the complexity of nonlinear time series over multiple time scales ...
Shijian Chen, Pengjian Shang
exaly   +2 more sources

Multivariate Weighted Multiscale Permutation Entropy for Complex Time Series

Nonlinear Dynamics, 2017
In this paper, we propose multivariate multiscale permutation entropy (MMPE) and multivariate weighted multiscale permutation entropy (MWMPE) to explore the complexity of the multivariate time series over multiple different time scales. First, we apply these methods to the simulated trivariate time series which is compose of white noise and 1/f noise ...
Yi Yin, Pengjian Shang
exaly   +2 more sources

Theoretical Study of Multiscale Permutation Entropy on Finite-Length Fractional Gaussian Noise

2018 26th European Signal Processing Conference (EUSIPCO), 2018
Permutation Entropy has been used as a robust and fast approach to calculate complexity of time series. There have been extensive studies on the properties and behavior of Permutation Entropy on known signals. Similarly, Multiscale Permutation Entropy has been used to analyze the structures at different time scales.
Philippe Ravier, Meryem Jabloun
exaly   +3 more sources

Multiscale Tsallis Permutation Entropy Analysis for Complex Physiological Time Series

Physica A: Statistical Mechanics and Its Applications, 2019
Abstract Discussing the complexity of time series has been a long-standing problem, including the use of information entropy to determine the complexity of the sequence. Permutation entropy (PE) has been regarded as a learning process to investigate the complexity of time series, such as financial time series and physiological time series.
Pengjian Shang
exaly   +2 more sources