Probabilistic Tools

  • Jean-François Mari
  • René Schott
Chapter

Abstract

In this chapter, we provide background material on probability theory.

Keywords

Markov Chain Hide Markov Model Markov Decision Process Large Deviation Principle Discrete Random Variable 
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.

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References

  1. [Feller, 1970]
    Feller, W. (1970). An Introduction To Probability Theory and Its Applications, volume 2 volumes. Wiley.Google Scholar
  2. [Revuz, 1975]
    Hida, T. (1980). Brownian Motion. Springer Verlag.Google Scholar
  3. [Revuz, 1975]
    Revuz, D. (1975). Markov Chains. North-Holland.Google Scholar
  4. [Bucklew, 1990]
    Bucklew, J. (1990). Large Deviations Techniques in Decision, Simulation, and Estimation. Wiley.Google Scholar
  5. [Dembo and Zeitouni, 1993]
    Dembo, A. and Zeitouni, O. (1993). Large Deviations and Applications. Jones and Barlet.Google Scholar
  6. [Stroock, 1984]
    Stroock, D. (1984). An Introduction to the Theory of Large Deviations. Springer Verlag.Google Scholar
  7. [Varadhan, 1984]
    Varadhan, S. (1984). Large Deviations and Applications. SIAM.Google Scholar

Copyright information

© Springer Science+Business Media New York 2001

Authors and Affiliations

  • Jean-François Mari
    • 1
  • René Schott
    • 2
  1. 1.LORIA and Université Nancy 2France
  2. 2.Université Henri Poincaré-Nancy 1France

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