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
Flutter and post-flutter constraints in aircraft design optimization
Eirikur Jonsson,Cristina Riso,Christopher A. Lupp,Carlos E. S. Cesnik,Joaquim R. R. A. Martins,Bogdan I. Epureanu +5 more
TL;DR: The methods for flutter analysis in the context of aircraft design optimization are reviewed and methods for predicting post-flutter limit cycle oscillations due to the increasing impact of nonlinear effects on future aircraft are included.
Journal ArticleDOI
An improved method for restraining the end effect in empirical mode decomposition and its applications to the fault diagnosis of large rotating machinery
Fangji Wu,Liangsheng Qu +1 more
TL;DR: In this article, an improved slope-based method (ISBM) is proposed to restrain the end effect in empirical mode decomposition (EMD) for non-stationary, nonlinear time series.
Journal ArticleDOI
Smart wind speed forecasting approach using various boosting algorithms, big multi-step forecasting strategy
TL;DR: All of the proposed hybrid models have better performance than the corresponding single forecasting models in the big multi-step predictions in the proposed new hybrid WPD-Boost-ENN-WPF framework.
Journal ArticleDOI
Empirical mode decomposition: a novel technique for the study of tremor time series
TL;DR: The application of the empirical mode decomposition (EMD) and Hilbert spectrum (HS), which are relatively new DSP techniques for the analysis of nonlinear and nonstationary time-series, for the study of tremor showed that the EMD could automatically decompose acquired signals into basic components, called intrinsic mode functions (IMFs), representing tremorous and voluntary activity.
Statistical significance test of intrinsic mode functions
Zhaohua Wu,Norden E. Huang +1 more
TL;DR: The characteristics of Gaussian white noise are studied by using the empirical mode decomposition (EMD) method and these methods are applied to well-studied geophysical datasets to demonstrate the method’s validity and effectiveness.
References
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Journal ArticleDOI
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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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Ensemble empirical mode decomposition: a noise-assisted data analysis method
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