• DocumentCode
    1098347
  • Title

    Application of approximation theory methods to recursive digital filter design

  • Author

    Chui, Charles K. ; Chan, Andrew K.

  • Author_Institution
    Texas A&M University, College Station, TX, USA
  • Volume
    30
  • Issue
    1
  • fYear
    1982
  • fDate
    2/1/1982 12:00:00 AM
  • Firstpage
    18
  • Lastpage
    24
  • Abstract
    In this paper, the ε-Herglotz tansform (or ε-outer function) is utilized to yield an analytic function \\hat{H}_{\\epsilon}(z) on the unit disk from the given amplitude characteristic of a digital filter. This is motivated by a two-fold objective: 1) the analytic function can be written in a power series expansion so that Padé approximants can be obtained and 2) \\hat{H}_{\\epsilon}(z) is a zero-free function in the Hardy space H2so that its polynomial least-squares inverse exists and does not vanish on the unit disk. Hence, we can immediately obtain recursive filters by Padé approximants and all-pole filters by means of least-squares inverses. There are two advantages in these methods: 1) we only need to solve linear systems of algebraic equations to obtain the filter coefficients; and 2) the phases of these filters exhibit almost linear in the passband, while the amplitude characteristics of these filters closely approximate the given one. If some adjustments are needed for the all-pole filters, we can use a standard least-squares technique to change an all-pole filter into a pole-zero filter. The detailed procedures are presented and the stability and approximation of these methods are discussed. Several examples are used for illustration purposes in this paper.
  • Keywords
    Approximation methods; Digital filters; Equations; Filtering theory; Fourier series; Hydrogen; Mathematics; Nonlinear filters; Passband; Stability;
  • fLanguage
    English
  • Journal_Title
    Acoustics, Speech and Signal Processing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0096-3518
  • Type

    jour

  • DOI
    10.1109/TASSP.1982.1163842
  • Filename
    1163842