- We will send in 10–14 business days.
/images/books/3393929/9780387768953.jpg)
- SAVE -10% with code: EXTRA
Reviews
Description
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).
EXTRA 10 % discount with code: EXTRA
The promotion ends in 17d.18:28:41
The discount code is valid when purchasing from 10 €. Discounts do not stack.
- Author: Alan Bain
- Publisher: Springer
- ISBN-10: 0387768955
- ISBN-13: 9780387768953
- Format: 23.6 x 16 x 2.5 cm, hardcover
- Language: English English
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).
Reviews