Articles liés à Dynamic Data Assimilation: A Least Squares Approach
Synopsis
A basic one-stop reference for graduate students and researchers.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
À propos des auteurs
John M. Lewis is a Research Scientist at the National Severe Storms Laboratory in Oklahoma, and the Desert Research Institute in Nevada.
S. Lakshmivarahan is a George Lynn Cross Research Professor at the School of Computer Science, University of Oklahoma.
Sudarshan K. Dhall is a Professor at the School of Computer Science, University of Oklahoma.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
- ÉditeurCambridge University Press
- Date d'édition2006
- ISBN 10 0521851556
- ISBN 13 9780521851558
- ReliureRelié
- Langueanglais
- Nombre de pages680
- Coordonnées du fabricantnon disponible
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Dynamic Data Assimilation: A Least Squares Approach (Encyclopedia of Mathematics and its Applications, Series Number 104)
Edité par
Cambridge University Press, 2006
ISBN 10 : 0521851556
ISBN 13 : 9780521851558
Neuf
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Dynamic Data Assimilation: A Least Squares Approach (Hardcover)
Edité par
Cambridge University Press, Cambridge, 2006
ISBN 10 : 0521851556
ISBN 13 : 9780521851558
Neuf
Couverture rigide
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Hardcover. Etat : new. Hardcover. 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 increasing importance in fields such as numerical weather prediction where conscientious efforts are being made to extend the term of reliable weather forecasts beyond the few days that are presently feasible. 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. Thus Part I is a broad introduction to the history, development and philosophy of data assimilation, illustrated by examples; Part II considers the classical, static approaches, both linear and nonlinear; and Part III describes computational techniques. Parts IV to VII are concerned with how statistical and dynamic ideas can be incorporated into the classical framework. Key themes covered here include estimation theory, stochastic and dynamic models, and sequential filtering. The final part addresses the predictability of dynamical systems. Chapters end with a section that provides pointers to the literature, and a set of exercises with instructive hints. A basic one-stop reference for graduate students and researchers. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability. N° de réf. du vendeur 9780521851558
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Dynamic Data Assimilation
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Cambridge University Press, 2008
ISBN 10 : 0521851556
ISBN 13 : 9780521851558
Neuf
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Gebunden. Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. A basic one-stop reference for graduate students and researchers. 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 sect. N° de réf. du vendeur 446950525
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Dynamic Data Assimilation: A Least Squares Approach (Encyclopedia of Mathematics and its Applications, Series Number 104)
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Cambridge University Press, 2006
ISBN 10 : 0521851556
ISBN 13 : 9780521851558
Neuf
Couverture rigide
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Hardcover. Etat : new. Excellent Condition.Excels in customer satisfaction, prompt replies, and quality checks. N° de réf. du vendeur Scanned0521851556
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Dynamic Data Assimilation: A Least Squares Approach
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Cambridge Univ Pr, 2006
ISBN 10 : 0521851556
ISBN 13 : 9780521851558
Neuf
Couverture rigide
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Hardcover. Etat : Brand New. 654 pages. 9.00x6.50x1.50 inches. In Stock. This item is printed on demand. N° de réf. du vendeur __0521851556
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Dynamic Data Assimilation: A Least Squares Approach (Encyclopedia of Mathematics and its Applications, Series Number 104)
Edité par
Cambridge University Press, 2006
ISBN 10 : 0521851556
ISBN 13 : 9780521851558
Neuf
Couverture rigide
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Dynamic Data Assimilation: A Least Squares Approach (Hardcover)
Edité par
Cambridge University Press, Cambridge, 2006
ISBN 10 : 0521851556
ISBN 13 : 9780521851558
Neuf
Couverture rigide
Vendeur : CitiRetail, Stevenage, Royaume-Uni
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Hardcover. Etat : new. Hardcover. 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 increasing importance in fields such as numerical weather prediction where conscientious efforts are being made to extend the term of reliable weather forecasts beyond the few days that are presently feasible. 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. Thus Part I is a broad introduction to the history, development and philosophy of data assimilation, illustrated by examples; Part II considers the classical, static approaches, both linear and nonlinear; and Part III describes computational techniques. Parts IV to VII are concerned with how statistical and dynamic ideas can be incorporated into the classical framework. Key themes covered here include estimation theory, stochastic and dynamic models, and sequential filtering. The final part addresses the predictability of dynamical systems. Chapters end with a section that provides pointers to the literature, and a set of exercises with instructive hints. A basic one-stop reference for graduate students and researchers. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. N° de réf. du vendeur 9780521851558
Quantité disponible : 1 disponible(s)
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Dynamic Data Assimilation: A Least Squares Approach (Encyclopedia of Mathematics and its Applications, Series Number 104)
Edité par
Cambridge University Press, 2006
ISBN 10 : 0521851556
ISBN 13 : 9780521851558
Neuf
Couverture rigide
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Dynamic Data Assimilation
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ISBN 10 : 0521851556
ISBN 13 : 9780521851558
Neuf
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Etat : New. pp. 680, Map, Index. N° de réf. du vendeur 26516600
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Dynamic Data Assimilation: A Least Squares Approach (Hardcover)
Edité par
Cambridge University Press, Cambridge, 2006
ISBN 10 : 0521851556
ISBN 13 : 9780521851558
Neuf
Couverture rigide
Vendeur : Grand Eagle Retail, Fairfield, OH, Etats-Unis
Évaluation du vendeur 5 sur 5 étoiles
Hardcover. Etat : new. Hardcover. 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 increasing importance in fields such as numerical weather prediction where conscientious efforts are being made to extend the term of reliable weather forecasts beyond the few days that are presently feasible. 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. Thus Part I is a broad introduction to the history, development and philosophy of data assimilation, illustrated by examples; Part II considers the classical, static approaches, both linear and nonlinear; and Part III describes computational techniques. Parts IV to VII are concerned with how statistical and dynamic ideas can be incorporated into the classical framework. Key themes covered here include estimation theory, stochastic and dynamic models, and sequential filtering. The final part addresses the predictability of dynamical systems. Chapters end with a section that provides pointers to the literature, and a set of exercises with instructive hints. A basic one-stop reference for graduate students and researchers. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. N° de réf. du vendeur 9780521851558
Quantité disponible : 1 disponible(s)