Performance of Discrete-Time Predictors of Continuous-Time Stationary Processes.

Abstract

This document studies the asymptotic performance of linear predictors of continuous-time stationary processes from observations at n sampling instants on a fixed observation interval. Considered are both optimal and simpler choices of predictor coefficients; uniform sampling, as well as nonuniform sampling tailored to the statistics of the process under prediction. The authors concentrate on stationary processes with rational spectral densities and obtain the asymptotic performance for cases with no and with one quadratic-mean derivative. The analytical results are supplemented by numerical examples depicting small and large sample size performance. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 1985
Accession Number
ADA166231

Entities

People

  • Elias Masry
  • Stamatis Cambanis

Organizations

  • University of North Carolina at Chapel Hill

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Abstracts
  • Air Force
  • Classification
  • Computations
  • Computer Science
  • Convergence
  • Covariance
  • Data Science
  • Information Science
  • Integral Equations
  • Markov Processes
  • North Carolina
  • Security
  • Stationary Processes
  • Statistics
  • Stochastic Processes
  • Two Dimensional

Fields of Study

  • Mathematics

Readers

  • Control Systems Engineering.
  • Regression Analysis.