Fractional Refined Composite Multiscale Fuzzy Entropy of International Stock Indices [PDF]
Entropy, 2019 Fractional refined composite multiscale fuzzy entropy (FRCMFE), which aims to relieve the large fluctuation of fuzzy entropy (FuzzyEn) measure and significantly discriminate different short-term financial time series with noise, is proposed to quantify ...
Zhiyong Wu, Wei Zhang
doaj +12 more sources
Composite Interpolation-Based Multiscale Fuzzy Entropy and Its Application to Fault Diagnosis of Rolling Bearing [PDF]
Entropy, 2019 Multiscale fuzzy entropy (MFE), as an enhanced multiscale sample entropy (MSE) method, is an effective nonlinear method for measuring the complexity of time series.
Qingyun Liu +4 more
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Entropy, 2023 The study focuses on the fault signals of rolling bearings, which are characterized by nonlinearity, periodic impact, and low signal-to-noise ratio.
Qiang Yuan +5 more
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Variable-Step Multiscale Fuzzy Dispersion Entropy: A Novel Metric for Signal Analysis
Entropy, 2023 Fuzzy dispersion entropy (FuzDE) is a newly proposed entropy metric, which combines the superior characteristics of fuzzy entropy (FE) and dispersion entropy (DE) in signal analysis.
Yuxing Li +4 more
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Improving Multiscale Fuzzy Entropy Robustness in EEG-Based Alzheimer’s Disease Detection via Amplitude Transformation [PDF]
SensorsThis study investigates the effectiveness of amplitude transformation in enhancing the performance and robustness of Multiscale Fuzzy Entropy for Alzheimer’s disease detection using electroencephalography signals. Multiscale Fuzzy Entropy is a complexity
Pasquale Arpaia +7 more
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A Multivariate Multiscale Fuzzy Entropy Algorithm with Application to Uterine EMG Complexity Analysis [PDF]
Entropy, 2016 The recently introduced multivariate multiscale entropy (MMSE) has been successfully used to quantify structural complexity in terms of nonlinear within- and cross-channel correlations as well as to reveal complex dynamical couplings and various degrees ...
Mosabber U. Ahmed +3 more
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Applying Improved Multiscale Fuzzy Entropy for Feature Extraction of MI-EEG [PDF]
Applied Sciences, 2017 Electroencephalography (EEG) is considered the output of a brain and it is a bioelectrical signal with multiscale and nonlinear properties. Motor Imagery EEG (MI-EEG) not only has a close correlation with the human imagination and movement intention but ...
Ming-ai Li +3 more
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Entropy, 2017 The vibration signals of rolling bearings are often nonlinear and non-stationary. Multiscale entropy (MSE) has been widely applied to measure the complexity of nonlinear mechanical vibration signals, however, at present only the single channel vibration ...
Jinde Zheng +5 more
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Multiscale Entropy Analysis of Short Signals: The Robustness of Fuzzy Entropy-Based Variants Compared to Full-Length Long Signals [PDF]
Entropy, 2021 Multiscale entropy (MSE) analysis is a fundamental approach to access the complexity of a time series by estimating its information creation over a range of temporal scales. However, MSE may not be accurate or valid for short time series.
Airton Monte Serrat Borin +3 more
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An Improved Composite Multiscale Fuzzy Entropy for Feature Extraction of MI-EEG [PDF]
Entropy, 2020 Motor Imagery Electroencephalography (MI-EEG) has shown good prospects in neurorehabilitation, and the entropy-based nonlinear dynamic methods have been successfully applied to feature extraction of MI-EEG.
Dongqin Xu, Mingai Li
exaly +6 more sources