• DocumentCode
    1484156
  • Title

    Linear recursive operator´s response using the discrete Fourier transform

  • Author

    Cadzow, James A.

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Vanderbilt Univ., Nashville, TN, USA
  • Volume
    16
  • Issue
    2
  • fYear
    1999
  • fDate
    3/1/1999 12:00:00 AM
  • Firstpage
    100
  • Lastpage
    114
  • Abstract
    A classic problem in signal processing is that of analysing empirical data in order to extract information contained within that data. The primary goal of this article is to employ the discrete Fourier transform (DFT) techniques for approximating, to a prescribed accuracy, the response of a shift-invariant recursive linear operator to a finite-length excitation. In this development, the required properties of the Fourier transform (FT) are first reviewed with particular attention directed toward the stable implementation of shift-invariant recursive linear operators. This is found to entail the decomposition of such operators into their causal and anticausal component operators. Subsequently, relevant issues related to the approximation of the FT by the DFT are examined. This includes the important properties of the non-uniqueness of mapping between a sequence and a given set of DFT coefficients. In the unit-impulse response approximation, DFT is shown to provide a useful means for approximating the unit-impulse response of a linear recursive operator. This includes making a partial fraction expansion of the operator´s frequency-response. The error incurred in using the DFT for effecting the unit-impulse response approximation is then treated. This error analysis involves the introduction of one-sided exponential sequences and their truncated mappings that arise in a natural fashion when employing the DFT. These concepts form the central theme of the article
  • Keywords
    approximation theory; discrete Fourier transforms; error analysis; mathematical operators; sequences; signal processing; transient response; DFT coefficients; anticausal component operator; causal component operator; discrete Fourier transform; empirical data analysis; error analysis; finite-length excitation; linear recursive operator response; one-sided exponential sequences; partial fraction expansion; shift-invariant recursive linear operator; signal processing; stable implementation; truncated mappings; unit-impulse response; Automatic control; Computational efficiency; Data analysis; Data mining; Discrete Fourier transforms; Fast Fourier transforms; Feedback; Signal processing; Stability; Statistical analysis;
  • fLanguage
    English
  • Journal_Title
    Signal Processing Magazine, IEEE
  • Publisher
    ieee
  • ISSN
    1053-5888
  • Type

    jour

  • DOI
    10.1109/79.752055
  • Filename
    752055