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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An analysis-forecast system for uncertainty modeling of wind speed: A case study of large-scale wind farms
TL;DR: In this article, an analysis-forecast system that includes an analysis module and a forecast module and can provide appropriate scenarios for the dispatching and scheduling of a power system is devised; this system superior to those presented in previous studies.
Journal ArticleDOI
Image empirical mode decomposition: a new tool for image processing
TL;DR: This study gives an overview of the state-of-the-art methods to decompose an image into a number of IMFs and a residue image with a minimum number of extrema points, together with the use of the method.
Journal ArticleDOI
Oscillatory processes in solar flares
Valery M. Nakariakov,Andrew Inglis,Ivan Zimovets,Claire Foullon,Erwin Verwichte,Robert Sych,Irina Myagkova +6 more
TL;DR: In this paper, the authors demonstrate that a promising novel method for their analysis is the empirical mode decomposition technique, which can be used to detect quasi-periodic pulsations (QPPs).
Journal ArticleDOI
Singular Spectrum Analysis for Effective Feature Extraction in Hyperspectral Imaging
TL;DR: A fast implementation of SSA (F-SSA) is proposed for efficient feature extraction in HSI that only needs one SVD applied to a representative pixel of the HSI hypercube, and the overall computational complexity has been significantly reduced.
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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