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2015 | OriginalPaper | Chapter

7. Filtering and Data Assimilation

Author : T. J. Sullivan

Published in: Introduction to Uncertainty Quantification

Publisher: Springer International Publishing

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Abstract

It is not bigotry to be certain we are right; but it is bigotry to be unable to imagine how we might possibly have gone wrong.

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previous chapter Bayesian Inverse Problems
next chapter Orthogonal Polynomials and Applications
Footnotes
1
That is, the LKF is iterative in the sense that it performs the state estimation sequentially with respect to the time steps; each individual update, however, is an elementary linear algebra problem, which could itself be solved either directly or iteratively.
 
2
There are many choices for this discrete-time model: each corresponds to a choice of numerical integration scheme for the underlying continuous-time ODE.
 
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Metadata
Title
Filtering and Data Assimilation
Author
T. J. Sullivan
Copyright Year
2015
Book
Introduction to Uncertainty Quantification

Print ISBN: 978-3-319-23394-9

Electronic ISBN: 978-3-319-23395-6

Copyright Year: 2015

DOI
https://doi.org/10.1007/978-3-319-23395-6_7