Results 21 to 30 of about 781,500 (170)

Refined composite multiscale fuzzy entropy based fault diagnosis of diesel engine

Journal of Low Frequency Noise, Vibration and Active Control, 2022
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, Xiao-Long Zhu, Wanzhong Li, Yedong Song, Yiming Zhang, Gengyi Lin, Guobin Pei, Jiewei Lin   +7 more
semanticscholar   +3 more sources

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

Measurement, 2023
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.
Andrea Cataldo, Sabatina Criscuolo, E. de Benedetto, Antonio Masciullo, Marisa Pesola, J. Picone, R. Schiavoni   +6 more
semanticscholar   +4 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

Multiscale Fuzzy Entropy Analysis of Balance: Evidences of Scale-Dependent Dynamics on Diabetic Patients With and Without Neuropathy

IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2023
Postural control is usually assessed by examining the fluctuations of the center of pressure (COP). Balance maintenance is based on sensory feedback and neural interactions, deployed over multiple temporal scales and producing less complex outputs with ...
Alessandro Mengarelli, Andrea Tigrini, Federica Verdini, Rosa Anna Rabini, Sandro Fioretti   +4 more
doaj   +2 more sources

Refined multiscale fuzzy entropy based on standard deviation for biomedical signal analysis [PDF]

Medical and Biological Engineering and Computing, 2017
Multiscale entropy (MSE) has been a prevalent algorithm to quantify the complexity of fluctuations in the local mean value of biomedical time series. Recent developments in the field have tried to improve the MSE by reducing its variability in large scale factors. On the other hand, there has been recent interest in using other statistical moments than
Hamed Azami, Alberto Fernández, Javier Escudero   +2 more
exaly   +5 more sources

A Novel Fault Detection Scheme Using Improved Inherent Multiscale Fuzzy Entropy With Partly Ensemble Local Characteristic-Scale Decomposition

IEEE Access, 2020
At present, the multiscale fuzzy entropy has been verified to be an excellent measure of the complexity for dynamic time series. However, when using to short-time time series collected in practical application, the conventional multiscale fuzzy entropy ...
Songrong Luo, Wenxian Yang, Youxin Luo
doaj   +2 more sources

Recognition of Biological Tissue Denaturation Based on Improved Multiscale Permutation Entropy and GK Fuzzy Clustering [PDF]

Information, 2022
Recognition of biological tissue denaturation is a vital work in high-intensity focused ultrasound (HIFU) therapy. Multiscale permutation entropy (MPE) is a nonlinear signal processing method for feature extraction, widely applied to the recognition of ...
Ziqi Peng, Xian Zhang, Jing Cao, Bei Liu
doaj   +3 more sources

Assessing the Role of EEG Biosignal Preprocessing to Enhance Multiscale Fuzzy Entropy in Alzheimer’s Disease Detection

Biosensors
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
Pasquale Arpaia, Maria Cacciapuoti, Andrea Cataldo, Sabatina Criscuolo, E. de Benedetto, Antonio Masciullo, Marisa Pesola, R. Schiavoni   +7 more
semanticscholar   +6 more sources

Quantifying Heart Rate Variability Using Multiscale Fuzzy Dispersion Entropy

IEEE Access
Heart rate variability (HRV), which is the variation of inter-beat intervals, exhibits complex characteristics on multiple temporal scales due to the balancing function of the autonomic nervous system.
Chae-Min Kim, Young-Seok Choi
doaj   +3 more sources

Cross‐domain bearing fault diagnosis with refined composite multiscale fuzzy entropy and the self organizing fuzzy classifier [PDF]

Engineering Reports, 2020
In this article, the use of refined composite multiscale fuzzy entropy (RCMFE) for cross‐domain diagnosis of bearings is introduced and verified with two publicly available datasets of varying operating conditions, a factor that challenges the diagnostic
Esther W. Gituku, J. Kimotho, J. Njiri
semanticscholar   +3 more sources