Journal ArticleDOI
The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis
Norden E. Huang,Zheng Shen,Steven R. Long,Man-Li C. Wu,Hsing H. Shih,Quanan Zheng,Nai-Chyuan Yen,C. C. Tung,Henry H. Liu +8 more
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TLDR
In this paper, a new method for analysing nonlinear and nonstationary data has been developed, which is the key part of the method is the empirical mode decomposition method with which any complicated data set can be decoded.Abstract:
A new method for analysing nonlinear and non-stationary data has been developed. The key part of the method is the empirical mode decomposition method with which any complicated data set can be dec...read more
Citations
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Artifact Removal in Physiological Signals—Practices and Possibilities
TL;DR: The physiological signals most likely to be recorded in the home are reviewed, documenting the artifacts which occur most frequently and which have the largest degrading effect, and a detailed analysis of current artifact removal techniques are presented.
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Application of Entropy Measures on Intrinsic Mode Functions for the Automated Identification of Focal Electroencephalogram Signals
TL;DR: The proposed method is able to differentiate the focal and non-focal EEG signals with an average classification accuracy of 87% correct and can be useful in assessing the nonlinear interrelation and complexity of focal and other EEG signals.
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Dislocated Time Series Convolutional Neural Architecture: An Intelligent Fault Diagnosis Approach for Electric Machine
TL;DR: Inspired by the idea of CNN, a novel diagnosis framework based on the characteristics of industrial vibration signals is developed, called dislocated time series CNN (DTS-CNN), which is composed of dislocate layer, convolutional layer, sub-sampling layer and fully connected layer.
Journal ArticleDOI
Time distortion associated with smartphone addiction: Identifying smartphone addiction via a mobile application (App)
Yu-Hsuan Lin,Yu Cheng Lin,Yang-Han Lee,Po Hsien Lin,Sheng-Hsuan Lin,Li-Ren Chang,Hsien Wei Tseng,Liang Yu Yen,Cheryl C.H. Yang,Terry B.J. Kuo,Terry B.J. Kuo +10 more
TL;DR: The study suggests the identification of smartphone addiction by diagnostic interview and via the App-generated parameters with EMD analysis, which suggests excessive use by daily use duration and frequency is associated with smartphone addiction.
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Vibration-based damage detection techniques used for health monitoring of structures: a review
TL;DR: In this paper, a comparative study among different vibration-based damage detection methods: fundamental modal examination, local diagnostic method, non-probabilistic methodology and the time series method was made.
References
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TL;DR: In this paper, the authors used the representations of the noise currents given in Section 2.8 to derive some statistical properties of I(t) and its zeros and maxima.
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