Dynamic data assimilation : a least squares approach /
Dynamic data assimilation is the assessment, combination and synthesis of observational data, scientific laws and mathematical models to determine the state of a complex physical system, for instance as a preliminary step in making predictions about the system's behaviour. The topic has assumed...
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| Main Authors: | , , |
|---|---|
| Format: | Electronic eBook |
| Language: | English |
| Published: |
Cambridge :
Cambridge University Press,
2006.
|
| Series: | Encyclopedia of mathematics and its applications ;
v. 104. |
| Subjects: | |
| Online Access: | CONNECT |
Table of Contents:
- 1. Synopsis
- 2. Pathways into data assimilation : illustrative examples
- 3. Applications
- 4. Brief history of data assimilation
- 5. Linear least squares estimation : method of normal equations
- 6. A geometric view : projection and invariance
- 7. Nonlinear least squares estimation
- 8. Recursive least squares estimation
- 9. Matrix methods
- 10. Optimization : steepest descent method
- 11. Conjugate direction/gradient methods
- 12. Newton and quasi-Newton methods
- 13. Principles of statistical estimation
- 14. Statistical least squares estimation
- 15. Maximum likelihood method
- 16. Bayesian estimation method
- 17. From Gauss to Kalman : sequential, linear minimum variance estimation.
