Multiple-view time-frequency distribution based on the empirical mode decomposition

Typeset version

 

TY  - JOUR
  - Stevenson, NJ,Mesbah, M,Boashash, B
  - 2010
  - January
  - Iet Signal Processing
  - Multiple-view time-frequency distribution based on the empirical mode decomposition
  - Validated
  - ()
  - HILBERT SPECTRUM
  - 4
  - 447
  - 456
  - This study proposes a novel, composite time-frequency distribution (TFD) constructed using a multiple-view approach. This composite TFD utilises the intrinsic mode functions (IMFs) of the empirical mode decomposition (EMD) to generate each view that are then combined using the arithmetic mean. This process has the potential to eliminate the inter-component interference generated by a quadratic TFD (QTFD), as the IMFs of the EMD are, in general, monocomponent signals. The formulation of the multiple-view TFD in the ambiguity domain results in faster computation, compared to a convolutive implementation in the time-frequency domain, and a more robust TFD in the presence of noise. The composite TFD, referred to as the EMD-TFD, was shown to generate a heuristically more accurate representation of the distribution of time-frequency energy in a signal. It was also shown to have performance comparable to the Wigner-Ville distribution when estimating the instantaneous frequency of multiple signal components in the presence of noise.
  - DOI 10.1049/iet-spr.2009.0084
DA  - 2010/01
ER  - 
@article{V70046780,
   = {Stevenson,  NJ and Mesbah,  M and Boashash,  B },
   = {2010},
   = {January},
   = {Iet Signal Processing},
   = {Multiple-view time-frequency distribution based on the empirical mode decomposition},
   = {Validated},
   = {()},
   = {HILBERT SPECTRUM},
   = {4},
  pages = {447--456},
   = {{This study proposes a novel, composite time-frequency distribution (TFD) constructed using a multiple-view approach. This composite TFD utilises the intrinsic mode functions (IMFs) of the empirical mode decomposition (EMD) to generate each view that are then combined using the arithmetic mean. This process has the potential to eliminate the inter-component interference generated by a quadratic TFD (QTFD), as the IMFs of the EMD are, in general, monocomponent signals. The formulation of the multiple-view TFD in the ambiguity domain results in faster computation, compared to a convolutive implementation in the time-frequency domain, and a more robust TFD in the presence of noise. The composite TFD, referred to as the EMD-TFD, was shown to generate a heuristically more accurate representation of the distribution of time-frequency energy in a signal. It was also shown to have performance comparable to the Wigner-Ville distribution when estimating the instantaneous frequency of multiple signal components in the presence of noise.}},
   = {DOI 10.1049/iet-spr.2009.0084},
  source = {IRIS}
}
AUTHORSStevenson, NJ,Mesbah, M,Boashash, B
YEAR2010
MONTHJanuary
JOURNAL_CODEIet Signal Processing
TITLEMultiple-view time-frequency distribution based on the empirical mode decomposition
STATUSValidated
TIMES_CITED()
SEARCH_KEYWORDHILBERT SPECTRUM
VOLUME4
ISSUE
START_PAGE447
END_PAGE456
ABSTRACTThis study proposes a novel, composite time-frequency distribution (TFD) constructed using a multiple-view approach. This composite TFD utilises the intrinsic mode functions (IMFs) of the empirical mode decomposition (EMD) to generate each view that are then combined using the arithmetic mean. This process has the potential to eliminate the inter-component interference generated by a quadratic TFD (QTFD), as the IMFs of the EMD are, in general, monocomponent signals. The formulation of the multiple-view TFD in the ambiguity domain results in faster computation, compared to a convolutive implementation in the time-frequency domain, and a more robust TFD in the presence of noise. The composite TFD, referred to as the EMD-TFD, was shown to generate a heuristically more accurate representation of the distribution of time-frequency energy in a signal. It was also shown to have performance comparable to the Wigner-Ville distribution when estimating the instantaneous frequency of multiple signal components in the presence of noise.
PUBLISHER_LOCATION
ISBN_ISSN
EDITION
URL
DOI_LINKDOI 10.1049/iet-spr.2009.0084
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