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
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Short-term photovoltaic power generation forecasting based on random forest feature selection and CEEMD: A case study
TL;DR: A hybrid forecasting model that combines random forest, improved grey ideal value approximation, complementary ensemble empirical mode decomposition, and particle swarm optimization algorithm is constructed, which proved that the RF-CEEMD-DIFPSO-BPNN is a promising approach in terms of PV power generation forecasting.
Journal ArticleDOI
New method for modal identification of super high‐rise building structures using discretized synchrosqueezed wavelet and Hilbert transforms
TL;DR: In this article, a new approach is presented for modal parameter identification of structures particularly suitable for very large real-life structures such as super high-rise building structures based on the integration of discretized synchrosqueezed wavelet transform, the Hilbert transform, and the linear least-square fit.
Journal ArticleDOI
Generalized empirical mode decomposition and its applications to rolling element bearing fault diagnosis
TL;DR: The analysis results indicate that the proposed method consisting of GEMD and EED is superior to the original HHT at least in restraining the boundary effect, gaining a better frequency resolution and more accurate components and time frequency distribution.
Journal ArticleDOI
Signal feature extraction based on an improved EMD method
Li Lin,Ji Hongbing +1 more
TL;DR: In this paper, an improved EMD method for signal feature extraction is proposed, where an inverse EMD filter scheme is used to obtain the optimal envelopes mean and a new sifting stop criterion is proposed to guarantee the orthogonality of the sifting results.
Journal ArticleDOI
Empirical Low-Rank Approximation for Seismic Noise Attenuation
TL;DR: The proposed empirical low-rank approximation method adaptively decompose the input data into several components that have truly low ranks via empirical mode decomposition and demonstrates the superior performance of the proposed approach over traditional alternatives.
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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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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