Fundamentals of stochastic filtering
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...
Enregistré dans:
| Auteurs principaux: | , |
|---|---|
| Format: | Livre numérique |
| Langue: | Anglais |
| Publié: |
New York, NY :
Springer New York : Springer e-books : Imprint: Springer : Springer e-books
[20..].
Cham : Springer Nature |
| Collection: | Stochastic modelling and applied probability
60 |
| Sujets: | |
| Accès en ligne: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
| Note: |
Description d'après consultation du 29 septembre 2011 Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Fundamentals of stochastic filtering, Alan Bain, Dan Crisan, 2009, New York, Springer, 1 vol. (XIII-390 p.), Stochastic modelling and applied probability, 978-1-4419-2642-5 |
Table des matières:
- Introduction The Stochastic Process The Filtering Equations Uniqueness of the Solution to the Zakai and the Kushner-Stratonovitch Equations Other results Finite Dimensional Filters The Density of the Conditional Distribution of the Signal Numerical Methods for Solving the Filtering Problem A Continuous Time Particle Filter Particle Filters in Discrete Time Measure Theory Stochastic Analysis References