Stationary Covariance Generation with Finite State Markov Processes,

Abstract

This paper studies the stationary covariance generation problem, i.e. the problem of passing from a stationary covariance function to a dynamical system which generates a process having the given covariance, in the case where the dynamical system is a finite state, continuous time, Markov process. Strictly positive definite stationary covariances can be approximated to any degree of accuracy in this way. However the number of states required may approach infinity as the covariance approaches the boundary of the set of positive definite functions.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1974
Accession Number
ADA046046

Entities

People

  • Roger W. Brockett

Organizations

  • Harvard University

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Coefficients
  • Covariance
  • Differential Equations
  • Eigenvalues
  • Equations
  • Markov Processes
  • Military Research
  • Numbers
  • Partial Differential Equations
  • Power Spectra
  • Probability
  • Spectra
  • Stationary
  • Steady State
  • Stochastic Processes
  • Theorems
  • Vector Spaces

Fields of Study

  • Engineering

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Statistical inference.