ENGLISH

Fundamentals of stochastic filtering

By Alan Bain , Dan Crisan (auth.)

Book information

Publisher
Springer-Verlag New York
Year
2009
ISBN
0387768955, 9780387768953
DOI
10.1007/978-0-387-76896-0
LCC
QA274 .B33 2009
Open Library ID
OL23202311M
Language
english
Format
PDF
Filesize
2 MB (2275888 bytes)
Series
Stochastic modelling and applied probability 60
Edition
1
Pages
390\395
Library
Kolxo3
Time added
2009-07-20 03:45:11
Mechatronics; Numerical Analysis; Quantitative FinProbability Theory and Stochastic Processes; ContrRobotics

Description

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 background to enable study of the recent literature. While no prior knowledge of stochastic filtering is required, readers are assumed to be familiar with measure theory, probability theory and the basics of stochastic processes. Most of the technical results that are required are stated and proved in the appendices. The book is intended as a reference for graduate students and researchers interested in the field. It is also suitable for use as a text for a graduate level course on stochastic filtering. Suitable exercises and solutions are included.

Similar books