Fundamentals of Stochastic Filtering
(Sprache: Englisch)
This book provides 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...
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Klappentext zu „Fundamentals of Stochastic Filtering “
This book provides 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. Exercises and solutions are included.
Inhaltsverzeichnis zu „Fundamentals of Stochastic Filtering “
Filtering Theory.- The Stochastic Process ?.- The Filtering Equations.- Uniqueness of the Solution to the Zakai and the Kushner-Stratonovich Equations.- The Robust Representation Formula.- Finite-Dimensional Filters.- The Density of the Conditional Distribution of the Signal.- Numerical Algorithms.- Numerical Methods for Solving the Filtering Problem.- A Continuous Time Particle Filter.- Particle Filters in Discrete Time.
Autoren-Porträt von Alan Bain, Dan Crisan
Dan Crisan is Reader in Mathematics at Imperial College London. His main research interest is stochastic filtering theory.
Bibliographische Angaben
- Autoren: Alan Bain , Dan Crisan
- 2008, 390 Seiten, Masse: 16,1 x 24,4 cm, Gebunden, Englisch
- Verlag: Springer, New York
- ISBN-10: 0387768955
- ISBN-13: 9780387768953
Sprache:
Englisch
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