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

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

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  • Author(s): N.J. Stevenson 1 ; M. Mesbah 2 ; B. Boashash 3
    • View affiliations
    • Affiliations: 1: Neonatal Brain Research Group, College of Medicine and Health, University College Cork, Cork, Ireland
      2: Centre for Clinical Research, Royal Brisbane and Women's Hospital, University of Queensland, Herston, Australia
      3: College of Engineering, University of Sharjah, Sharjah, UAE
  • Source: Volume 4, Issue 4, August 2010, p. 447 – 456
    DOI:  10.1049/iet-spr.2009.0084 , Print ISSN 1751-9675, Online ISSN 1751-9683
© The Institution of Engineering and Technology
Published

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.

Inspec keywords: sonar signal processing; radar signal processing

Other keywords: composite time-frequency; TFD; empirical mode decomposition; multiple-view time-frequency distribution; EMD; multiple signal components; radar signal processing; sonar signal processing; time- frequency domain; Wigner-Ville distribution

Subjects: Sonar and acoustic radar; Signal processing and detection; Radar equipment, systems and applications

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