Statistical Design of Autoregressive-Moving Average Digital Filters

Abstract

Procedures are presented for the systematic design of digital filters that contain poles and zeros. The procedures are simple, fast, and effective. All of the important algorithms are of the Levinson-type. The first key idea in the paper is that one may begin a design by posing a linear prediction problem for a stochastic sequence. The second is that a high-order 'whitening' filter may be constructed for this sequence and 'inverted' to yield a high-order all- pole filter whose spectrum approximates the spectrum of the stochastic sequence. The third key idea is that the all-pole filter may be used to generate consistent unit pulse and convariance sequences for use in the Mullis-Roberts algorithm. This algorithm is then used to obtain a low-order digital filter with poles and zeros that approximates the high-order all-pole filter. The results demonstrate that the Mullis-Roberts algorithm, together with the design philosophy of this paper, may be used with profit to reduce filter complexity and to design spectrum-matching digital filters.

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Document Details

Document Type
Technical Report
Publication Date
Apr 01, 1977
Accession Number
ADA039970

Entities

People

  • James C. Luby
  • Louis L. Louis L. Scharf
  • M. M. Siddiqui

Organizations

  • Colorado State University

Tags

Communities of Interest

  • Energy and Power Technologies
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Algorithms
  • Coefficients
  • Covariance
  • Digital Filters
  • Electrical Engineering
  • Equations
  • Filters
  • Frequency
  • Frequency Response
  • Military Research
  • Power Spectra
  • Signal Processing
  • Spectra
  • Statistics
  • Transfer Functions
  • United States
  • United States Government

Fields of Study

  • Engineering

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Approximation Theory.