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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Journal ArticleDOI
Multiwavelet transform and its applications in mechanical fault diagnosis – A review
TL;DR: This paper attempts to summarize the recent development of multiwavelet transform and its applications in mechanical fault diagnosis to construct an image of the contributions of different generation multiwavelets and link the current frontiers with engineering applications for readers interested in this field.
Journal ArticleDOI
A new envelope algorithm of Hilbert-Huang Transform
Shuren Qin,Y.M. Zhong +1 more
TL;DR: A new envelope algorithm, the segment power function method, is put forward that is superior to existing algorithms because in most situations it is more flexible than the cubic spline interpolation algorithm and smoother than the Akima interpolation algorithms, and it is less likely to introduce a false frequency when applied to HHT.
Journal ArticleDOI
Application of the EMD method in the vibration analysis of ball bearings
Qiuhua Du,Shunian Yang +1 more
TL;DR: In this article, the empirical mode decomposition (EMD) method is introduced and the calculation of the local mean with the envelope method of the extrema is substituted by an improved method, in which the local means is computed by using the average method of successive extremas.
Journal ArticleDOI
Short-term wind speed prediction using an extreme learning machine model with error correction
TL;DR: Three experimental results show that: the error correction is effective in decreasing the prediction error, and the proposed models with error correction are suitable for short-term wind speed forecasting; the ICEEMDAN method is more powerful than other variants of empirical mode decomposition in performing non-stationary decomposition, and
Journal ArticleDOI
Noninvasive cuffless blood pressure estimation using pulse transit time and Hilbert-Huang transform
TL;DR: The relationship between blood pressure and PTT is illustrated, the problems of calibration and re-calibration are discussed, and the multi-innovation recursive least square algorithm is employed to update the unknown parameter vector for the model and improve the results.
References
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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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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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