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
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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Ensemble Classification and Regression-Recent Developments, Applications and Future Directions [Review Article]
TL;DR: This paper reviews traditional as well as state-of-the-art ensemble methods and thus can serve as an extensive summary for practitioners and beginners.
Journal ArticleDOI
A novel bearing fault diagnosis model integrated permutation entropy, ensemble empirical mode decomposition and optimized SVM
TL;DR: In this paper, a hybrid model for fault detection and classification of motor bearing is presented, where the permutation entropy (PE) of the vibration signal is calculated to detect the malfunctions of the bearing.
Journal ArticleDOI
The Synchrosqueezing algorithm for time-varying spectral analysis
TL;DR: It is shown that Synchrosqueezing is robust to bounded perturbations of the signal and to Gaussian white noise, which justifies its applicability to noisy or nonuniformly sampled data that is ubiquitous in engineering and the natural sciences.
Journal ArticleDOI
Evolution of land surface air temperature trend
TL;DR: In this paper, the authors used the spatial-temporally multidimensional ensemble empirical mode decomposition method to diagnose the evolution of global land surface air temperature trend in the past century.
Journal ArticleDOI
Multi-step forecasting for wind speed using a modified EMD-based artificial neural network model
TL;DR: The developed model shows the best accuracy comparing with basic FNN and unmodified EMD-based FNN through multi-step forecasting the mean monthly and daily wind speed in Zhangye of China.
References
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Journal ArticleDOI
Deterministic nonperiodic flow
TL;DR: In this paper, it was shown that nonperiodic solutions are ordinarily unstable with respect to small modifications, so that slightly differing initial states can evolve into considerably different states, and systems with bounded solutions are shown to possess bounded numerical solutions.
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TL;DR: In this paper, a general overview of the nonlinear theory of water wave dynamics is presented, including the Wave Equation, the Wave Hierarchies, and the Variational Method of Wave Dispersion.
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RANDOM DATA Analysis and Measurement Procedures
TL;DR: A revised and expanded edition of this classic reference/text, covering the latest techniques for the analysis and measurement of stationary and nonstationary random data passing through physical systems, is presented in this article.
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Mathematical analysis of random noise
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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Ensemble empirical mode decomposition: a noise-assisted data analysis method
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