Data analysis using a combination of independent component analysis and empirical mode decomposition

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Title:	Data analysis using a combination of independent component analysis and empirical mode decomposition
Authors:	Lin,SL;Tung,PC;Huang,NE
Contributors:	機械工程研究所
Keywords:	NONSTATIONARY TIME-SERIES;BLIND SEPARATION;ALGORITHM
Date:	2009
Issue Date:	2010-06-29 18:01:31 (UTC+8)
Publisher:	中央大學
Abstract:	A combination of independent component analysis and empirical mode decomposition (ICA-EMD) is proposed in this paper to analyze low signal-to-noise ratio data. The advantages of ICA-EMD combination are these: ICA needs few sensory clues to separate the original source from unwanted noise and EMD can effectively separate the data into its constituting parts. The case studies reported here involve original sources contaminated by white Gaussian noise. The simulation results show that the ICA-EMD combination is an effective data analysis tool.
Relation:	PHYSICAL REVIEW E
Appears in Collections:	[Graduate Institute of Mechanical Engineering] journal & Dissertation

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