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 +2 more
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Fault Diagnosis of Wind Turbine Gearbox Based on Improved Multivariate Variational Mode Decomposition and Ensemble Refined Composite Multivariate Multiscale Dispersion Entropy [PDF]
EntropyWind turbine planetary gearboxes have complex structures and operating environments, which makes it difficult to extract fault features effectively. In addition, it is difficult to achieve efficient fault diagnosis.
Xin Xia, Xiaolu Wang, Weilin Chen
doaj +5 more sources
Intra- and Inter-Regional Complexity in Multi-Channel Awake EEG Through Multivariate Multiscale Dispersion Entropy for Assessing Sleep Quality and Aging [PDF]
BiosensorsAging and poor sleep quality are associated with altered brain dynamics, yet current electroencephalography (EEG) analyses often overlook regional complexity.
Ahmad Zandbagleh +5 more
doaj +4 more sources
A Refined Composite Multivariate Multiscale Fluctuation Dispersion Entropy and Its Application to Multivariate Signal of Rotating Machinery [PDF]
Entropy, 2021 In the fault monitoring of rotating machinery, the vibration signal of the bearing and gear in a complex operating environment has poor stationarity and high noise.
Chenbo Xi +4 more
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Refined Composite Multivariate Multiscale Dispersion Entropy and Its Application to Fault Diagnosis of Rolling Bearing [PDF]
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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Jixie chuandong, 2021 When the gearbox fails， its vibration signal is unstable and nonlinear. The commonly applied gearbox fault diagnosis methods are almost all based on the single-channel vibration signal analysis，which is easy to cause the loss of fault information，so the ...
Fuming Zhou +4 more
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Stratified Multivariate Multiscale Dispersion Entropy for Physiological Signal Analysis [PDF]
IEEE Transactions on Biomedical Engineering, 2023 Multivariate entropy quantification algorithms are becoming a prominent tool for the extraction of information from multi-channel physiological time-series. However, in the analysis of physiological signals from heterogeneous organ systems, certain channels may overshadow the patterns of others, resulting in information loss.
Evangelos Kafantaris +2 more
openaire +5 more sources
IEEE Access, 2022 This paper proposes an Improved Multivariate Multiscale Dispersion Entropy(IMMDE) combined with Hierarchical Entropy(HE) for vibration signal feature extraction.
Zhuang Tang, Jie Liu, Chaofeng Li
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Graph-Based Multivariate Multiscale Dispersion Entropy: Efficient Implementation and Applications to Real-World Network Data [PDF]
CoRRWe introduce Multivariate Multiscale Graph-based Dispersion Entropy (mvDEG), a novel, computationally efficient method for analyzing multivariate time series data in graph and complex network frameworks, and demonstrate its application in real-world data.
Fabila-Carrasco, John Stewart +2 more
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Alexandria Engineering Journal, 2022 The processing of ship radiated noise is a research hotspot in the field of military and marine resource exploration. Frequency characteristic is an important characteristic of ship radiated noise.
Guohui Li, Yongming Hou, Hong Yang
doaj +2 more sources