A Note on Covariance-Invariant Digital Filter Design and Autoregressive Moving Average Spectrum Analysis.

Abstract

Consider an autoregressive-moving average (ARMA) discrete-time sequence (x sub k) with covariance sequence (R sub k). The results are derived and presented somewhat differently than usual to complement the results for the synthesis of covariance-invariant digital filters. In the context of spectrum analysis, the results provide a means of performing ARMA spectrum analysis on data that arise as sampled data from a rational continuous-time process. An important result, shows that the ARMA spectrum can be obtained without actually solving the nonlinear factorization problem for the MA coefficients.

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Document Details

Document Type
Technical Report
Publication Date
Nov 01, 1978
Accession Number
ADA061916

Entities

People

  • Allen R. Stubberud
  • John F. Kinkel
  • Joseph Perl
  • Louis L. Louis L. Scharf

Organizations

  • Colorado State University

Tags

Communities of Interest

  • Energy and Power Technologies
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Covariance
  • Data Science
  • Digital Filters
  • Electrical Engineering
  • Engineering
  • Filters
  • Information Science
  • Military Research
  • Power Spectra
  • Probability
  • Signal Processing
  • Spectra
  • Spectrum Analysis
  • Statistics
  • Transfer Functions
  • United States
  • United States Government

Readers

  • Approximation Theory.
  • Statistical inference.