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Functional Analysis for Probability and Stochastic Processes

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Functional Analysis for Probability and Stochastic Processes

Functional Analysis for Probability and Stochastic Processes

392 pages, parution le 11/08/2005

Résumé

This text is designed both for students of probability and stochastic processes, and for students of functional analysis. For the reader not familiar with functional analysis a detailed introduction to necessary notions and facts is provided. However, this is not a straight textbook in functional analysis; rather, it presents some chosen parts of functional analysis that can help understand ideas from probability and stochastic processes. The subjects range from basic Hilbert and Banach spaces, through weak topologies and Banach algebras, to the theory of semigroups of bounded linear operators. Numerous standard and non-standard examples and exercises make the book suitable as a course textbook or for self-study.

  • Numerous standard and non-standard examples and exercises make the book suitable for both a textbook for a course as well as for self-study
  • Unique in content, range, structure and presentation
  • Very detailed clear and careful proofs

Sommaire

  • Preface
  • Preliminaries, notations, conventions
  • Basic notations in functional analysis
  • Conditional expectation
  • Brownian motion and hilbert spaces
  • Dual spaces and convergence of probability measures
  • The Gelfand transform and its applications
  • Semigroups of operators and Lévy processes
  • Markov processes and semigroups of operators
  • Appendixes
  • References
  • Index
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Caractéristiques techniques du livre "Functional Analysis for Probability and Stochastic Processes"

  PAPIER
Éditeur(s) Cambridge University Press
Auteur(s) Adam Bobrowski
Parution 11/08/2005
Nb. de pages 392
Format 15 x 23
Couverture Broché
Poids 654g
Intérieur Noir et Blanc
EAN13 9780521539371
ISBN13 978-0-521-53937-1

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