• DocumentCode
    2189129
  • Title

    Complex empirical mode decomposition, Hilbert-Huang transform, and fourier transform applied to moving objects

  • Author

    Wallis, Kristen ; Akers, Geoffrey ; Collins, Peter ; Davis, Richard ; Frazier, Alan ; Oxley, Mark ; Terzuoli, Andrew

  • Author_Institution
    Air Force Inst. of Technol., Wright-Patterson AFB, OH, USA
  • fYear
    2012
  • fDate
    22-27 July 2012
  • Firstpage
    4395
  • Lastpage
    4398
  • Abstract
    A review of current signal analysis tools show that new techniques are required for an enhanced fidelity or data integrity. Recently, the Hilbert-Huang transform (HHT) and its inherent property, the Empirical Mode Decomposition (EMD) technique, have been formerly investigated. The technique of Complex EMD (CEMD) was also explored. The scope of this work was to assess the CEMD technique as an innovative analysis tool. Subsequent to this, comparisons between applications of the Hilbert transform (HT) and the Fast-Fourier transform (FFT) were analyzed. MATLAB® was implemented to model signal decomposition and the execution of mathematical transforms for generating results. The CEMD technique successfully decomposed the data into its oscillatory modes. After comparative graphical analysis of the HT and FFT, application of the HT provided marginal enhancements of the data modeled previously by the FFT. Altogether, the HHT could not be determined as a helpful analysis tool. Nevertheless, the CEMD technique, an inherent component of the HHT, exhibited a possible improvement as an analysis tool for signal processing data. Further evaluation of the CEMD technique and the HHT is needed for ultimate determination of their usefulness as an analysis tool.
  • Keywords
    Hilbert transforms; data integrity; fast Fourier transforms; signal processing; Hilbert-Huang transform; complex empirical mode decomposition technique; data integrity; enhanced fidelity; fast Fourier transform; mathematical transforms; model signal decomposition; moving object; signal analysis tools; Diffusion tensor imaging; Fourier transforms; Remote sensing; Signal processing; Signal processing algorithms; Empirical mode decomposition; Fourier transform; Hilbert transform; remote sensing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Geoscience and Remote Sensing Symposium (IGARSS), 2012 IEEE International
  • Conference_Location
    Munich
  • ISSN
    2153-6996
  • Print_ISBN
    978-1-4673-1160-1
  • Electronic_ISBN
    2153-6996
  • Type

    conf

  • DOI
    10.1109/IGARSS.2012.6350399
  • Filename
    6350399