Optimal Sampling Rates for Auto Regressive Models.

Abstract

In time series analysis a particular model for a linear system is an auto-regression model. Auto-regression models are particularly well suited to structural linear systems which have been persistently excited by white noise. The white noise is assumed to be unmeasurable and it is assumed that there is no measurement noise. The variability of the results obtained in practice tends to depend on the sampling rates used. This memo examines in detail the asymptotic convariance matrix for estimates of the damping rate and frequency for a fixed length of record and variable sampling rates in a linear system which is completely described, in continuous time, by a single second order differential equation. It is shown that the selection of sampling rate plays an extremely important role in the quality of estimates. Keywords: Australia; Parameter identification; Least squares method.

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Document Details

Document Type
Technical Report
Publication Date
Apr 01, 1986
Accession Number
ADA168740

Entities

People

  • T. G. Ryall

Tags

Communities of Interest

  • Air Platforms

DTIC Thesaurus Topics

  • Air Force
  • Australia
  • Civil Engineering
  • Department Of Defense
  • Differential Equations
  • Eigenvalues
  • Engineering
  • Equations
  • Frequency
  • Least Squares Method
  • Linear Systems
  • Mechanical Engineering
  • Noise
  • Sampling
  • Time Series Analysis
  • Universities
  • White Noise

Fields of Study

  • Mathematics

Readers

  • Approximation Theory.
  • Computational Modeling and Simulation