• DocumentCode
    2494629
  • Title

    Quadrivariate Empirical Mode Decomposition

  • Author

    Rehman, Naveed Ur ; Mandic, Danilo P.

  • Author_Institution
    Dept. of Electr. & Electron. Eng., Imperial Coll. London, London, UK
  • fYear
    2010
  • fDate
    18-23 July 2010
  • Firstpage
    1
  • Lastpage
    7
  • Abstract
    We introduce a quadrivariate extension of Empirical Mode Decomposition (EMD) algorithm, termed QEMD, as a tool for the time-frequency analysis of nonlinear and non-stationary signals consisting of up to four channels. The local mean estimation of the quadrivariate signal is based on taking real-valued projections of the input in different directions in a multidimensional space where the signal resides. To this end, the set of direction vectors is generated on 3-sphere (residing in 4D space) via the low-discrepancy Hammersley sequence. It has also been shown that the resulting set of vectors is more uniformly distributed on a 3-sphere as compared to that generated by a uniform angular coordinate system. The ability of QEMD to extract common modes within multichannel data is demonstrated by simulations on both synthetic and real-world signals.
  • Keywords
    Hilbert transforms; multidimensional signal processing; time-frequency analysis; QEMD; local mean estimation; low discrepancy Hammersley sequence; multichannel data; multidimensional space; nonstationary signal; quadrivariate empirical mode decomposition; quadrivariate signal; real valued projection; time frequency analysis; uniform angular coordinate system; EEG artifact separation; Empirical mode decomposition (EMD); Intrinsic mode functions (IMFs); Quadrivariate signal analysis; RGB image decomposition; multi-scale analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks (IJCNN), The 2010 International Joint Conference on
  • Conference_Location
    Barcelona
  • ISSN
    1098-7576
  • Print_ISBN
    978-1-4244-6916-1
  • Type

    conf

  • DOI
    10.1109/IJCNN.2010.5596768
  • Filename
    5596768