Fundamentals of stochastic filtering /

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Bibliographic Details
Author / Creator:Bain, Alan.
Imprint:New York ; London : Springer, 2009.
Description:1 online resource (xiii, 390 p.)
Series:Stochastic modelling and applied probability ; 60
Stochastic modelling and applied probability ; 60.
Subject:Stochastic processes.
Filters (Mathematics)
Control Engineering.
Numerical analysis.
Probability Theory and Stochastic Processes.
Quantitative Finance.
MATHEMATICS -- Probability & Statistics -- General.
Filters (Mathematics)
Stochastic processes.
Electronic books.
Format: E-Resource Book
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Other authors / contributors:Crisan, Dan.
Notes:Includes bibliographical references (p. [367]-382) and indexes.
Summary:The objective of stochastic filtering is to determine the best estimate for the state of a stochastic dynamical system from partial observations. The solution of this problem in the linear case is the well known Kalman-Bucy filter which has found widespread practical application. The purpose of this book is to provide a rigorous mathematical treatment of the non-linear stochastic filtering problem using modern methods. Particular emphasis is placed on the theoretical analysis of numerical methods for the solution of the filtering problem via particle methods. The book should provide sufficient
Other form:Print version: Bain, Alan. Fundamentals of stochastic filtering. New York : Springer, c2009 9780387768953