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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Journal ArticleDOI
A multiscale analysis for carbon price drivers
TL;DR: In this article, a multiscale analysis model was proposed to explore and identify the carbon price drivers at different timescales by introducing the latest multivariate empirical mode decomposition, carbon price and its potential drivers are decomposed into several groups of simple modes with specific economic meanings.
Proceedings ArticleDOI
A novel approach of fast and adaptive bidimensional empirical mode decomposition
TL;DR: Simulation results demonstrate that besides reducing the computation time, FABEMD outperforms the original BEMD in terms of the quality in some cases.
Journal ArticleDOI
Improved EMD-Based Complex Prediction Model for Wind Power Forecasting
Oveis Abedinia,Mohamed Lotfi,Mehdi Bagheri,Behrouz Sobhani,Miadreza Shafie-khah,Joao P. S. Catalao +5 more
TL;DR: A novel improved version of empirical mode decomposition (IEMD) to decompose wind measurements is proposed to demonstrate the superiority of the proposed method for wind forecasting compared to other methods for all test cases.
Journal ArticleDOI
On the quantification of heart rate variability spectral parameters using time-frequency and time-varying methods
TL;DR: This paper is an excursus through the most common time–frequency/time-varying representation of the HRV signal with a special emphasis on the algorithms employed for the reliable quantification of the LF and HF parameters and their tracking.
Proceedings ArticleDOI
Empirical Mode Decomposition - an introduction
TL;DR: The contribution reviews the technique of EMD and related algorithms and discusses illustrative applications.
References
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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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