Results 21 to 30 of about 808,398 (185)

An Improved Composite Multiscale Fuzzy Entropy for Feature Extraction of MI-EEG. [PDF]

Entropy (Basel), 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. Especially based on Multiscale Fuzzy Entropy (MFE), the fuzzy entropies of the τ coarse-grained sequences in τ scale are calculated and averaged to
Li M, Wang R, Xu D.
europepmc   +6 more sources

Intelligent Fault Diagnosis for Rotating Mechanical Systems: An Improved Multiscale Fuzzy Entropy and Support Vector Machine Algorithm

Algorithms
Rotating mechanical systems (RMSs) are widely applied in various industrial fields. Intelligent fault diagnosis technology plays a significant role in improving the reliability and safety of industrial equipment.
Yuxin Pan, Yinsheng Chen, Xihong Fei, Kang Wang, Tian Fang, Jing Wang   +5 more
doaj   +2 more sources

Composite Multiscale Fractional Fuzzy Diversity Entropy and Its Application in Bearing Fault Identification

Fractal and Fractional
This paper presents an intelligent fault identification approach integrating composite multiscale fractional fuzzy diversity entropy (CMFFDE) for feature extraction, joint mutual information (JMI) for feature selection, and an extreme learning machine ...
Xiong Gan, Guangyou Yang
doaj   +2 more sources

Multivariate Multiscale Dispersion Entropy of Biomedical Times Series [PDF]

Entropy, 2019
Due to the non-linearity of numerous physiological recordings, non-linear analysis of multi-channel signals has been extensively used in biomedical engineering and neuroscience.
Hamed Azami, Alberto Fernández, Javier Escudero   +2 more
doaj   +2 more sources

Multiscale fuzzy entropy based on local mean decomposition and Fisher rule for EEG feature extraction in human motion analysis [PDF]

EAI Endorsed Transactions on Scalable Information Systems, 2022
Electroencephalogram (EEG) is a nonlinear, non-stationary, and random weak signal generated by a large number of neurons. It has great research value and practical significance in artificial intelligence, biomedical engineering
Huili He
doaj   +1 more source

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, Anne Humeau-Heurtier, Luiz Otavio Murta, Luiz Eduardo Virgilio Silva   +3 more
openaire   +1 more source

Intelligent Fault Diagnosis of Rolling Bearings Based on a Complete Frequency Range Feature Extraction and Combined Feature Selection Methodology

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, Yukun Huang, Wanyang Zhang, Jinchuan Shi, Huageng Luo   +4 more
doaj   +1 more source

EEG complexity-based algorithm using Multiscale Fuzzy Entropy: Towards a detection of Alzheimer’s disease

Measurement
Alzheimer's Disease (AD) is a progressive neurodegenerative condition causing memory, attention, and language decline. Current AD diagnostic methods lack objectivity and non-invasiveness. While electroencephalography (EEG) holds promise for AD research, conventional EEG analysis methods have proven unsatisfactory.
Cataldo A., Criscuolo S., De Benedetto E., Masciullo A., Pesola M., Picone J., Schiavoni R.   +6 more
openaire   +4 more sources

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, Xiao Wang 0047, Jingjing Yang, Wei Zhang 0138, Sanyuan Zhang   +4 more
openaire   +2 more sources

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