• DocumentCode
    3116048
  • Title

    Subspace-Based Blind Identification of IIR Systems

  • Author

    Gómez, Juan C. ; Baeyens, Enrique

  • Author_Institution
    Lab. for Syst. Dynamics & Signal Process., Univ. Nac. de Rosario, Rosario
  • fYear
    2006
  • fDate
    6-8 Sept. 2006
  • Firstpage
    97
  • Lastpage
    102
  • Abstract
    A new subspace method for the blind identification of infinite impulse response (IIR), single input-multiple output (SIMO) systems represented using orthonormal bases with fixed poles, is presented in this paper. Basis coefficients are estimated in closed form, up to a scalar factor, by first computing the column space of the output Hankel matrix using singular value decomposition (SVD), and then solving a least squares problem also resorting to an SVD. The performance of the proposed algorithm is illustrated through a simulation example.
  • Keywords
    Hankel matrices; IIR filters; least mean squares methods; singular value decomposition; infinite impulse response; least squares problem; output Hankel matrix; single input-multiple output systems; singular value decomposition; subspace-based blind identification; Computational modeling; Digital communication; Finite impulse response filter; Least squares approximation; Matrix decomposition; Sensor arrays; Signal processing; Signal processing algorithms; Singular value decomposition; Stability;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning for Signal Processing, 2006. Proceedings of the 2006 16th IEEE Signal Processing Society Workshop on
  • Conference_Location
    Arlington, VA
  • ISSN
    1551-2541
  • Print_ISBN
    1-4244-0656-0
  • Electronic_ISBN
    1551-2541
  • Type

    conf

  • DOI
    10.1109/MLSP.2006.275529
  • Filename
    4053628