• DocumentCode
    492181
  • Title

    Structure Constrained PARAFAC Model with Application to Signal Processing

  • Author

    Liu, Xu ; Xu, Zongze

  • Author_Institution
    Coll. of Info. Sci. & Tech., Nanjing Univ. of Aeronaut. & Astronaut., Nanjing
  • fYear
    2008
  • fDate
    21-22 Dec. 2008
  • Firstpage
    651
  • Lastpage
    654
  • Abstract
    Structure constrained parallel factor (PARAFAC) model, which combines the structural property of communication signal with the PARAFAC analysis, was presented in this paper. The uniqueness property of the model was discussed and developed. Structure constrained trilinear alternative least square (SCTALS) algorithm was proposed to fit the constrained model. Simulation results showed that, compared to the normal PARAFAC model, the structure constrained PARAFAC was more suitable to describe communication signal. The blind signal processing algorithm based on the constrained model had better fitting performance, and still worked well in some conditions where the normal PARAFAC-based algorithm failed.
  • Keywords
    blind source separation; least squares approximations; matrix decomposition; PARAFAC model; blind signal processing algorithm; structure constrained parallel factor model; structure constrained trilinear alternative least square algorithm; two-way matrix decomposition; Array signal processing; Data analysis; Educational institutions; Fitting; Least squares methods; Psychometric testing; Signal analysis; Signal processing; Signal processing algorithms; Wireless communication; PARAFAC model; blind signal processing; structure constraint; uniqueness property;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Knowledge Acquisition and Modeling Workshop, 2008. KAM Workshop 2008. IEEE International Symposium on
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-1-4244-3530-2
  • Electronic_ISBN
    978-1-4244-3531-9
  • Type

    conf

  • DOI
    10.1109/KAMW.2008.4810573
  • Filename
    4810573