Advertisement

Markov Chains pp 253-322 | Cite as

Gibbs Fields and Monte Carlo Simulation

  • Pierre Brémaud
Chapter
Part of the Texts in Applied Mathematics book series (TAM, volume 31)

Abstract

The Markov property of a stochastic sequence {X n } n ≥0 implies that for all n ≥ 1, X n is independent of (X k , k ∉ {n − 1, n, n + 1)) given (X n −1, X n +1).

Keywords

Monte Carlo Simulation Simulated Annealing Monte Carlo Markov Chain Random Field Transition Matrix 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Copyright information

© Springer Science+Business Media New York 1999

Authors and Affiliations

  • Pierre Brémaud
    • 1
  1. 1.Laboratoire des Signaux et SystèmesCNRS-ESEGif-sur-YvetteFrance

Personalised recommendations