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
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Refined Composite Multiscale Fuzzy Dispersion Entropy and Its Applications to Bearing Fault Diagnosis [PDF]
Entropy, 2023 Rotary machines often exhibit nonlinear behavior due to factors such as nonlinear stiffness, damping, friction, coupling effects, and defects. Consequently, their vibration signals display nonlinear characteristics.
Mostafa Rostaghi +3 more
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Fault Diagnosis of Planetary Gearbox Based on Hierarchical Refined Composite Multiscale Fuzzy Entropy and Optimized LSSVM [PDF]
EntropyEfficient extraction and classification of fault features remain critical challenges in planetary gearbox fault diagnosis. A fault diagnosis framework is proposed that integrates hierarchical refined composite multiscale fuzzy entropy (HRCMFE) for ...
Xin Xia, Xiaolu Wang
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A Refined Composite Multivariate Multiscale Fuzzy Entropy and Laplacian Score-Based Fault Diagnosis Method for Rolling Bearings [PDF]
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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Refined composite multiscale fuzzy entropy based fault diagnosis of diesel engine
Journal of Low Frequency Noise, Vibration and Active Control, 2023 Due to complicated transfer paths and strong background noise interference, the fault pattern information deeply hides in common features of the vibration signal at the engine surface. In this study, the refined composite multiscale fuzzy entropy (RCMFE)
Junhong Zhang +7 more
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Entropy, 2021 Bearing vibration signals typically have nonlinear components due to their interaction and coupling effects, friction, damping, and nonlinear stiffness. Bearing faults affect the signal complexity at various scales.
Mostafa Rostaghi +3 more
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Evaluation of entropy features and classifier performance in person authentication using resting-state EEG [PDF]
Frontiers in NeuroscienceIntroductionResting-state electroencephalogram (EEG) presents a promising biometric modality due to its inherent liveness detection and resistance to spoofing, addressing critical vulnerabilities in conventional systems.
Renyu Yang +8 more
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A Novel Gear Fault Diagnosis Method Based on COA-VMD, RCMFE and SSA-BP [PDF]
EntropyAiming at the difficulties in extracting gear fault feature information and the unsatisfactory performance of commonly used machine learning classification models in terms of feature separability and stable within-distribution recognition, this paper ...
Duowen Chen +7 more
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IEEE Access, 2019 Many nonlinear dynamic and statistic methods, including multiscale sample entropy (MSE) and multiscale fuzzy entropy (MFE), have been widely studied and employed to fault diagnosis of the rolling bearing. Multiscale dispersion entropy (MDE) is a powerful
Congzhi Li +4 more
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