Results 21 to 30 of about 1,556 (171)
Characterizing Network Anomaly Traffic with Euclidean Distance-Based Multiscale Fuzzy Entropy [PDF]
Security and Communication Networks, 2021 The prosperity of mobile networks and social networks brings revolutionary conveniences to our daily lives. However, due to the complexity and fragility of the network environment, network attacks are becoming more and more serious. Characterization of network traffic is commonly used to model and detect network anomalies and finally to raise the ...
Renjie Zhou +4 more
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Sensors, 2023 The utilization of multiscale entropy methods to characterize vibration signals has proven to be promising in intelligent diagnosis of mechanical equipment.
Zhengkun Xue +4 more
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Multiscale Entropy Analysis of Short Signals: The Robustness of Fuzzy Entropy-Based Variants [PDF]
, 2021 Abstract 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 Refined Composite Multivariate Multiscale Fuzzy Entropy Method for MI-EEG Feature Extraction. [PDF]
Comput Intell Neurosci, 2019 Feature extraction of motor imagery electroencephalogram (MI-EEG) has shown good application prospects in the field of medical health. Also, multivariate entropy-based feature extraction methods have been gradually applied to analyze complex multichannel biomedical signals, such as EEG and electromyography.
Li M, Wang R, Yang J, Duan L.
europepmc +3 more sources
Complexity, 2021 Refined composite multivariate multiscale fractional fuzzy entropy (RCmvMFFE), which aims to sensitively discriminate different short noisy multichannel financial data, is proposed as a new measure to quantify the complexity dynamics of multichannel time
Huiqin Chu, Zhiyong Wu, Wei Zhang
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Rolling Bearing Fault Diagnosis Based on VMD-MPE and PSO-SVM
Entropy, 2021 The goal of the paper is to present a solution to improve the fault detection accuracy of rolling bearings. The method is based on variational mode decomposition (VMD), multiscale permutation entropy (MPE) and the particle swarm optimization-based ...
Maoyou Ye, Xiaoan Yan, Minping Jia
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Refined Multiscale Entropy Using Fuzzy Metrics: Validation and Application to Nociception Assessment [PDF]
Entropy, 2019 The refined multiscale entropy (RMSE) approach is commonly applied to assess complexity as a function of the time scale. RMSE is normally based on the computation of sample entropy (SampEn) estimating complexity as conditional entropy. However, SampEn is dependent on the length and standard deviation of the data.
José F. Valencia +5 more
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Assessing the Role of EEG Biosignal Preprocessing to Enhance Multiscale Fuzzy Entropy in Alzheimer's Disease Detection. [PDF]
Biosensors (Basel)Quantitative electroencephalography (QEEG) has emerged as a promising tool for detecting Alzheimer’s disease (AD). Among QEEG measures, Multiscale Fuzzy Entropy (MFE) shows great potential in identifying AD-related changes in EEG complexity. However, MFE is intrinsically linked to signal amplitude, which can vary substantially among EEG systems, and ...
Arpaia P +7 more
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Refined Multiscale Fuzzy Entropy to Analyse Post-Exercise Cardiovascular Response in Older Adults With Orthostatic Intolerance. [PDF]
Entropy (Basel), 2018 Orthostatic intolerance syndrome occurs when the autonomic nervous system is incapacitated and fails to respond to the demands associated with the upright position. Assessing this syndrome among the elderly population is important in order to prevent falls. However, this problem is still challenging.
Hortelano M +3 more
europepmc +8 more sources
Entropy, 2022 The extension of sample entropy methodologies to multivariate signals has received considerable attention, with traditional univariate entropy methods, such as sample entropy (SampEn) and fuzzy entropy (FuzzyEn), introduced to measure the complexity of ...
Hongjian Xiao +2 more
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