Trend extraction based on separations of consecutive empirical mode decomposition components in Hilbert marginal spectrum

Yang, Zhijing and Ling, Bingo Wing-Kuen and Bingham, Chris (2013) Trend extraction based on separations of consecutive empirical mode decomposition components in Hilbert marginal spectrum. Measurement: Journal of the International Measurement Confederation, 46 (8). pp. 2481-2491. ISSN 0263-2241

Full content URL: http://dx.doi.org/10.1016/j.measurement.2013.04.07...

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Item Type:Article
Item Status:Live Archive

Abstract

Extracting the underlying trends is an important tool for the analysis of signals. This paper presents a novel methodology for extracting the underlying trends of signals based on the separations of consecutive empirical mode decomposition (EMD) components in the Hilbert marginal spectrum. A signal is initially represented as a sum of intrinsic mode functions (IMFs) obtained via the EMD. The Hilbert marginal spectrum of each IMF is then calculated. The separations of two consecutive IMFs in the Hilbert marginal spectrum are estimated based on their correlation coefficients. The group of the last several IMFs in which the IMFs are close to each other in the Hilbert marginal spectrum will be used for the representation of the underlying trend of the signal. Extensive experimental results are presented to illustrate the rationale and the effectiveness of the proposed method. © 2013 Elsevier Ltd. All rights reserved.

Keywords:Analysis of signal, Correlation coefficient, Empirical Mode Decomposition, Hilbert marginal spectrum, Intrinsic Mode functions, Novel methodology, Trend extractions, Extraction, Functions, Signal processing
Subjects:H Engineering > H100 General Engineering
Divisions:College of Science > School of Engineering
ID Code:11401
Deposited On:04 Sep 2013 12:26

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