Fully Nonparametric Regression Estimation Based on Empirical Mode Decomposition

Hong Ying Hu; Wen Long Li; Feng Qiang Zhao

doi:10.4028/www.scientific.net/AMM.271-272.932

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 271-272Fully Nonparametric Regression Estimation Based on...

Fully Nonparametric Regression Estimation Based on Empirical Mode Decomposition

Abstract:

Empirical Mode Decomposition (EMD) is a non-stationary signal processing method developed recently. It has been applied in many engineering fields. EMD has many similarities with wavelet decomposition. But EMD Decomposition has its own characteristics, especially in accurate trend extracting. Therefore the paper firstly proposes an algorithm of extracting slow-varying trend based on EMD. Then, according to wavelet regression estimation method, a new regression function estimation method based on EMD is presented. The simulation proves the advantages of the approach with easy computation and more accurate result.

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Periodical:

Applied Mechanics and Materials (Volumes 271-272)

Pages:

932-935

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.271-272.932

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Online since:

December 2012

Authors:

Hong Ying Hu, Wen Long Li, Feng Qiang Zhao

Keywords:

Empirical Mode Decomposition (EMD), Regression Estimation, Wavelet

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