A novel gaussian window approach for empirical mode decomposition

Shuen-De Wu, Chiu Wen Wu, Cha Lin Liu, Yan Hao Huang, Kung Yen Lee

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Empirical mode decomposition (EMD) is an algorithmic construction for decomposing multi-component signals into a series of intrinsic mode functions (IMFs). However, traditional EMD may encounter the difficulty of mode mixing when a signal contains intermittency. To solve the difficulty, a Gaussian window averaging method is proposed to construct the mean envelope of a given signal in each sifting process. The numerical analysis also demonstrates promising reliability with the proposed algorithm.

Original languageEnglish
Title of host publicationAdvanced Materials and Engineering Materials
Pages274-277
Number of pages4
DOIs
Publication statusPublished - 2012 Feb 21
Event2011 International Conference on Advanced Materials and Engineering Materials, ICAMEM2011 - Shenyang, Liaoning, China
Duration: 2011 Nov 222011 Nov 24

Publication series

NameAdvanced Materials Research
Volume457-458
ISSN (Print)1022-6680

Other

Other2011 International Conference on Advanced Materials and Engineering Materials, ICAMEM2011
CountryChina
CityShenyang, Liaoning
Period11/11/2211/11/24

Fingerprint

Decomposition
Numerical analysis

Keywords

  • Empirical mode decomposition
  • Gaussian
  • Intrinsic mode function
  • Mode mixing

ASJC Scopus subject areas

  • Engineering(all)

Cite this

Wu, S-D., Wu, C. W., Liu, C. L., Huang, Y. H., & Lee, K. Y. (2012). A novel gaussian window approach for empirical mode decomposition. In Advanced Materials and Engineering Materials (pp. 274-277). (Advanced Materials Research; Vol. 457-458). https://doi.org/10.4028/www.scientific.net/AMR.457-458.274

A novel gaussian window approach for empirical mode decomposition. / Wu, Shuen-De; Wu, Chiu Wen; Liu, Cha Lin; Huang, Yan Hao; Lee, Kung Yen.

Advanced Materials and Engineering Materials. 2012. p. 274-277 (Advanced Materials Research; Vol. 457-458).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Wu, S-D, Wu, CW, Liu, CL, Huang, YH & Lee, KY 2012, A novel gaussian window approach for empirical mode decomposition. in Advanced Materials and Engineering Materials. Advanced Materials Research, vol. 457-458, pp. 274-277, 2011 International Conference on Advanced Materials and Engineering Materials, ICAMEM2011, Shenyang, Liaoning, China, 11/11/22. https://doi.org/10.4028/www.scientific.net/AMR.457-458.274
Wu S-D, Wu CW, Liu CL, Huang YH, Lee KY. A novel gaussian window approach for empirical mode decomposition. In Advanced Materials and Engineering Materials. 2012. p. 274-277. (Advanced Materials Research). https://doi.org/10.4028/www.scientific.net/AMR.457-458.274
Wu, Shuen-De ; Wu, Chiu Wen ; Liu, Cha Lin ; Huang, Yan Hao ; Lee, Kung Yen. / A novel gaussian window approach for empirical mode decomposition. Advanced Materials and Engineering Materials. 2012. pp. 274-277 (Advanced Materials Research).
@inproceedings{ebd39db4212e4f94b3d7f7cb787b5faf,
title = "A novel gaussian window approach for empirical mode decomposition",
abstract = "Empirical mode decomposition (EMD) is an algorithmic construction for decomposing multi-component signals into a series of intrinsic mode functions (IMFs). However, traditional EMD may encounter the difficulty of mode mixing when a signal contains intermittency. To solve the difficulty, a Gaussian window averaging method is proposed to construct the mean envelope of a given signal in each sifting process. The numerical analysis also demonstrates promising reliability with the proposed algorithm.",
keywords = "Empirical mode decomposition, Gaussian, Intrinsic mode function, Mode mixing",
author = "Shuen-De Wu and Wu, {Chiu Wen} and Liu, {Cha Lin} and Huang, {Yan Hao} and Lee, {Kung Yen}",
year = "2012",
month = "2",
day = "21",
doi = "10.4028/www.scientific.net/AMR.457-458.274",
language = "English",
isbn = "9783037853559",
series = "Advanced Materials Research",
pages = "274--277",
booktitle = "Advanced Materials and Engineering Materials",

}

TY - GEN

T1 - A novel gaussian window approach for empirical mode decomposition

AU - Wu, Shuen-De

AU - Wu, Chiu Wen

AU - Liu, Cha Lin

AU - Huang, Yan Hao

AU - Lee, Kung Yen

PY - 2012/2/21

Y1 - 2012/2/21

N2 - Empirical mode decomposition (EMD) is an algorithmic construction for decomposing multi-component signals into a series of intrinsic mode functions (IMFs). However, traditional EMD may encounter the difficulty of mode mixing when a signal contains intermittency. To solve the difficulty, a Gaussian window averaging method is proposed to construct the mean envelope of a given signal in each sifting process. The numerical analysis also demonstrates promising reliability with the proposed algorithm.

AB - Empirical mode decomposition (EMD) is an algorithmic construction for decomposing multi-component signals into a series of intrinsic mode functions (IMFs). However, traditional EMD may encounter the difficulty of mode mixing when a signal contains intermittency. To solve the difficulty, a Gaussian window averaging method is proposed to construct the mean envelope of a given signal in each sifting process. The numerical analysis also demonstrates promising reliability with the proposed algorithm.

KW - Empirical mode decomposition

KW - Gaussian

KW - Intrinsic mode function

KW - Mode mixing

UR - http://www.scopus.com/inward/record.url?scp=84863158952&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84863158952&partnerID=8YFLogxK

U2 - 10.4028/www.scientific.net/AMR.457-458.274

DO - 10.4028/www.scientific.net/AMR.457-458.274

M3 - Conference contribution

AN - SCOPUS:84863158952

SN - 9783037853559

T3 - Advanced Materials Research

SP - 274

EP - 277

BT - Advanced Materials and Engineering Materials

ER -