Stochastic Evolution Systems | Linear Theory and Applications to Non-Linear Filtering. Cet article n’est pas disponible.
Langue : anglais
Edité par Springer, 2018
Série : Livre 21 sur 35 - Probability Theory and Stochastic Modelling
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- Neuf
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A propos de cet article
Stochastic Evolution Systems | Linear Theory and Applications to Non-Linear Filtering | Boris L. Rozovsky (u. a.) | Taschenbuch | xvi | Englisch | 2018 | Springer | EAN 9783030069339 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
N° de réf. du vendeur 117467116
- Titre
- Stochastic Evolution Systems | Linear Theory and Applications to Non-Linear Filtering
- Auteur
- Boris L. Rozovsky (u. a.)
- Éditeur
- Springer
- Année de publication
- 2018
- État de l'article
- Neu
- Reliure
- Taschenbuch
- Langue
- anglais
- ISBN à 10 chiffres
- 3030069338
- ISBN à 13 chiffres
- 9783030069339
- Édition
- 2ème Édition
- Poids de l'article
- 528 grammes
- Dimensions
- 235 x 155 x 19 mm
- Série
- Livre 21 sur 35: Probability Theory and Stochastic Modelling
- Catalogues du vendeur
- Bücher
This monograph, now in a thoroughly revised second edition, develops the theory of stochastic calculus in Hilbert spaces and applies the results to the study of generalized solutions of stochastic parabolic equations.
The emphasis lies on second-order stochastic parabolic equations and their connection to random dynamical systems. The authors further explore applications to the theory of optimal non-linear filtering, prediction, and smoothing of partially observed diffusion processes. The new edition now also includes a chapter on chaos expansion for linear stochastic evolution systems.
This book will appeal to anyone working in disciplines that require tools from stochastic analysis and PDEs, including pure mathematics, financial mathematics, engineering and physics.
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À propos de l’auteur
Boris Rozovsky earned a Master's degree in Probability and Statistics, followed by a PhD in Physical and Mathematical Sciences, both from the Moscow State (Lomonosov) University. He was Professor of Mathematics and Director of the Center for Applied Mathematical Sciences at the University of Southern California. Currently, he is the Ford Foundation Professor of Applied Mathematics at Brown University.
Sergey Lototsky earned a Master's degree in Physics in 1992 from the Moscow Institute of Physics and Technology, followed by a PhD in Applied Mathematics in 1996 from the University of Southern California. After a year-long post-doc at the Institute for Mathematics and its Applications and a three-year term as a Moore Instructor at MIT, he returned to the department of Mathematics at USC as a faculty member in 2000. He specializes in stochastic analysis, with emphasis on stochastic differential equation. He supervised more than 10 PhD students and had visiting positions at the Mittag-Leffler Institute in Sweden and at several universities in Israel and Italy.
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