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- Toujours un magasin près de chez vous
Stochastic Analysis for Gaussian Random Processes and Fields
With Applications
Vidyadhar S Mandrekar, Leszek Gawarecki
135,95 €
+ 271 points
Format
Description
Stochastic Analysis for Gaussian Random Processes and Fields: With Applications presents Hilbert space methods to study deep analytic properties connecting probabilistic notions. In particular, it studies Gaussian random fields using reproducing kernel Hilbert spaces (RKHSs).
The book begins with preliminary results on covariance and associated RKHS before introducing the Gaussian process and Gaussian random fields. The authors use chaos expansion to define the Skorokhod integral, which generalizes the Itô integral. They show how the Skorokhod integral is a dual operator of Skorokhod differentiation and the divergence operator of Malliavin. The authors also present Gaussian processes indexed by real numbers and obtain a Kallianpur-Striebel Bayes' formula for the filtering problem. After discussing the problem of equivalence and singularity of Gaussian random fields (including a generalization of the Girsanov theorem), the book concludes with the Markov property of Gaussian random fields indexed by measures and generalized Gaussian random fields indexed by Schwartz space. The Markov property for generalized random fields is connected to the Markov process generated by a Dirichlet form.
Spécifications
Parties prenantes
- Auteur(s) :
- Editeur:
Contenu
- Nombre de pages :
- 202
- Langue:
- Anglais
- Collection :
Caractéristiques
- EAN:
- 9781498707817
- Date de parution :
- 23-06-15
- Format:
- Livre relié
- Format numérique:
- Genaaid
- Dimensions :
- 157 mm x 234 mm
- Poids :
- 680 g
