Overview
- Develops new methods of deterministic numerical integration
- Derives and describes state of the art filter algorithms
- Presents methods of deterministic numerical integration
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Table of contents (6 chapters)
Keywords
- Kalman filter
- Recursive Bayesian estimation
- State-space models
- Smolyak cubature
- Numerical integration
- Cubature Kalman filter
- Maximum Likelihood estimation
- Deterministic numerical integration
- Univariate non-stationary growth model
- Six-dimentional coordinated turn model
- Lorenz model
- Ginzburg-Landau model
- Optimization and stabilization of cubature rules
- Smolyak cubature rules with an approximate degree of exactness
- Filtering in dynamical systems
About this book
The book addresses the problem of calculation of d-dimensional integrals (conditional expectations) in filter problems. It develops new methods of deterministic numerical integration, which can be used to speed up and stabilize filter algorithms. With the help of these methods, better estimates and predictions of latent variables are made possible in the fields of economics, engineering and physics. The resulting procedures are tested within four detailed simulation studies.
Authors and Affiliations
About the author
Bibliographic Information
Book Title: Stable and Efficient Cubature-based Filtering in Dynamical Systems
Authors: Dominik Ballreich
DOI: https://doi.org/10.1007/978-3-319-62130-2
Publisher: Springer Cham
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: Springer International Publishing AG 2017
Hardcover ISBN: 978-3-319-62129-6Published: 06 September 2017
Softcover ISBN: 978-3-319-87239-1Published: 12 May 2018
eBook ISBN: 978-3-319-62130-2Published: 28 August 2017
Edition Number: 1
Number of Pages: XVII, 160
Number of Illustrations: 5 b/w illustrations, 14 illustrations in colour
Topics: Statistics for Business, Management, Economics, Finance, Insurance, Econometrics, Computational Mathematics and Numerical Analysis, Vibration, Dynamical Systems, Control, Statistical Physics and Dynamical Systems