Modal Decomposition of Covariance Sequences for Parametric Spectrum Analysis.

Abstract

In this paper we make the point that a wide variety of spectrum types admit to modal analysis wherein the modes are characterized by amplitudes, frequencies, and damping factors. The associated modal decomposition is appropriate for both continuous and discrete components of the spectrum. The domain of attraction for the decomposition includes ARMA sequences, harmonically- or nonharmonically-related sinusoids, damped sinusoids, white noise, and linear combinations of these. Numerical results are presented to illustrate the identification of mode parameters and corresponding spectra from finite records of perfect and estimated covariance sequences. The results for sinusoids and sinusoids in white noise are interpreted in terms of in phase and quadrature effects attributable to the finite record length. (Author)

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Mar 01, 1981
Accession Number
ADA095099

Entities

People

  • A. A. Louis Beex
  • Louis L. Louis L. Scharf
  • Timothy Von Reyn

Organizations

  • Colorado State University

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Algorithms
  • Colorado
  • Contracts
  • Covariance
  • Data Science
  • Electrical Engineering
  • Engineering
  • Equations
  • Frequency
  • Information Science
  • Military Research
  • Probability
  • Spectrum Analysis
  • Statistics
  • United States
  • Universities
  • White Noise

Fields of Study

  • Engineering

Readers

  • Atmospheric Science / Meteorology, specifically Wind Wave Turbulence.
  • Statistical inference.
  • Structural Dynamics.