Dynamic Data Assimilation

A Least Squares Approach

John M. Lewis, S. Lakshmivarahan, S.K. Dhall - Collection Encyclopedia of Mathematics and its Applications

654 pages, parution le 03/08/2006

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Résumé

Dynamic data assimilation is the assessment, combination and synthesis of observational data, scientific laws and mathematical models to make predictions about how a complex physical system will behave.

This book is designed to be a basic one-stop reference for graduate students and researchers. It is based on graduate courses taught over a decade to mathematicians, scientists, and engineers, and its modular structure accommodates the various audience requirements.

Chapters end with a section that provides pointers to the literature, and a set of exercises with instructive hints. Computation is encouraged: algorithms are liberally scattered throughout the text. Accompanying refresher material - in many areas of mathematics including vector spaces, optimization and probability theory - will be available from www.cambridge.org/0521851556. The book ends with a comprehensive bibliography.

Sommaire

Preface
Acknowledgments
Genesis of Data Assimilation
Data Assimilation: Deterministic/Static Models
Computational Techniques
Statistical Estimation
Data Assimilation: Stochastic/Static Models
Data Assimilation: Deterministic/Dynamic Models
Data Assimilation: Stochastic/Dynamic Models
Predictability
Epilogue
Appendices
References
Index

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Caractéristiques techniques

	PAPIER
Éditeur(s)	Cambridge University Press
Auteur(s)	John M. Lewis, S. Lakshmivarahan, S.K. Dhall
Collection	Encyclopedia of Mathematics and its Applications
Parution	03/08/2006
Nb. de pages	654
Format	16 x 24
Couverture	Relié
Poids	1101g
Intérieur	Noir et Blanc
EAN13	9780521851558
ISBN13	978-0-521-85155-8