Convergence Properties of Continuous-Time Markov Chains with Application to Target Search

Abstract

This paper considers the search for targets modeled as a discrete state, continuous-time Markov process. Convergence properties are analyzed using the eigenvalues and eigenvectors of a state transition rate matrix without explicitly solving differential equations or calculating matrix exponentials. It also studies the effect of cueing on convergence rate using eigenvalue analysis and optimal control theoretic approach.

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Document Details

Document Type
Technical Report
Publication Date
May 01, 2005
Accession Number
ADA434223

Entities

People

  • David E. Jeffcoat
  • Myungsoo Jun

Organizations

  • Air Force Research Laboratory

Tags

Communities of Interest

  • Air Platforms
  • Autonomy
  • Ground and Sea Platforms
  • Materials and Manufacturing Processes
  • Weapons Technologies

DTIC Thesaurus Topics

  • Air Force
  • Air Force Research Laboratories
  • Aircrafts
  • Convergence
  • Detection
  • Differential Equations
  • Eigenvalues
  • Eigenvectors
  • Equations
  • Markov Chains
  • Markov Processes
  • Mathematics
  • Operations Research
  • Probability
  • Search Theory
  • Stochastic Processes
  • Transitions

Readers

  • Computational Modeling and Simulation
  • Linear Algebra
  • Sensor Fusion and Tracking Systems.