Enhanced empirical mode decomposition using a novel sifting-based interpolation points detection

Yannis Kopsinis; Stephen McLaughlin

doi:10.1109/SSP.2007.4301354

Enhanced empirical mode decomposition using a novel sifting-based interpolation points detection

Yannis Kopsinis^*, Stephen McLaughlin

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

17 Citations (Scopus)

Abstract

Empirical mode decomposition (EMD) is a signal analysis method which has received much attention lately due its performance in a number of applications. The main disadvantage of EMD is that it is lacking a theoretical foundation and therefore, our understanding of it have come through intuition and experimental validation. This drawback has significantly limited the potential for improvements to the method itself. In other words, the version of EMD currently used by most researchers is roughly the same as that proposed 9 years ago. In this paper, a novel version of EMD is proposed which exhibits significantly improved decomposition performance. This new development exploits the results of a study on EMD concerning the optimized configuration of EMD with respect to criteria for selection of interpolation points.

Original language	English
Title of host publication	2007 IEEE/SP 14th Workshop on Statistical Signal Processing
Publisher	IEEE
Pages	725-729
Number of pages	5
ISBN (Electronic)	9781424411986
ISBN (Print)	9781424411979
DOIs	https://doi.org/10.1109/SSP.2007.4301354
Publication status	Published - 2007
Event	14th IEEE/SP WorkShoP on Statistical Signal Processing 2007 - Madison, United States Duration: 26 Aug 2007 → 29 Aug 2007

Conference

Conference	14th IEEE/SP WorkShoP on Statistical Signal Processing 2007
Abbreviated title	SSP 2007
Country/Territory	United States
City	Madison
Period	26/08/07 → 29/08/07

Keywords

Signal analysis
Signal decomposition
Time - Frequency analysis

ASJC Scopus subject areas

Signal Processing

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10.1109/SSP.2007.4301354

Cite this

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title = "Enhanced empirical mode decomposition using a novel sifting-based interpolation points detection",

abstract = "Empirical mode decomposition (EMD) is a signal analysis method which has received much attention lately due its performance in a number of applications. The main disadvantage of EMD is that it is lacking a theoretical foundation and therefore, our understanding of it have come through intuition and experimental validation. This drawback has significantly limited the potential for improvements to the method itself. In other words, the version of EMD currently used by most researchers is roughly the same as that proposed 9 years ago. In this paper, a novel version of EMD is proposed which exhibits significantly improved decomposition performance. This new development exploits the results of a study on EMD concerning the optimized configuration of EMD with respect to criteria for selection of interpolation points.",

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language = "English",

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T1 - Enhanced empirical mode decomposition using a novel sifting-based interpolation points detection

AU - Kopsinis, Yannis

AU - McLaughlin, Stephen

PY - 2007

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N2 - Empirical mode decomposition (EMD) is a signal analysis method which has received much attention lately due its performance in a number of applications. The main disadvantage of EMD is that it is lacking a theoretical foundation and therefore, our understanding of it have come through intuition and experimental validation. This drawback has significantly limited the potential for improvements to the method itself. In other words, the version of EMD currently used by most researchers is roughly the same as that proposed 9 years ago. In this paper, a novel version of EMD is proposed which exhibits significantly improved decomposition performance. This new development exploits the results of a study on EMD concerning the optimized configuration of EMD with respect to criteria for selection of interpolation points.

AB - Empirical mode decomposition (EMD) is a signal analysis method which has received much attention lately due its performance in a number of applications. The main disadvantage of EMD is that it is lacking a theoretical foundation and therefore, our understanding of it have come through intuition and experimental validation. This drawback has significantly limited the potential for improvements to the method itself. In other words, the version of EMD currently used by most researchers is roughly the same as that proposed 9 years ago. In this paper, a novel version of EMD is proposed which exhibits significantly improved decomposition performance. This new development exploits the results of a study on EMD concerning the optimized configuration of EMD with respect to criteria for selection of interpolation points.

KW - Signal analysis

KW - Signal decomposition

KW - Time - Frequency analysis

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DO - 10.1109/SSP.2007.4301354

M3 - Conference contribution

AN - SCOPUS:47849113130

SN - 9781424411979

SP - 725

EP - 729

BT - 2007 IEEE/SP 14th Workshop on Statistical Signal Processing

PB - IEEE

T2 - 14th IEEE/SP WorkShoP on Statistical Signal Processing 2007

Y2 - 26 August 2007 through 29 August 2007

ER -

Enhanced empirical mode decomposition using a novel sifting-based interpolation points detection

Abstract

Conference

Keywords

ASJC Scopus subject areas

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