Dynamic Data Assimilation Hardback: A Least Squares Approach: 104 (Encyclopedia of Mathematics and its Applications, Series Number 104) - Tapa dura

Lewis; Lakshmivarahan; Dhall

9780521851558: Dynamic Data Assimilation Hardback: A Least Squares Approach: 104 (Encyclopedia of Mathematics and its Applications, Series Number 104)

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ISBN 10: 0521851556 ISBN 13: 9780521851558

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A basic one-stop reference for graduate students and researchers.

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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.

"Sobre este t�tulo" puede pertenecer a otra edici�n de este libro.

EditorialCambridge University Press
A�o de publicaci�n2006
ISBN 10 0521851556
ISBN 13 9780521851558
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Dynamic Data Assimilation: A Least Squares Approach (Encyclopedia of Mathematics and its Applications, Series Number 104)

Lewis, John M.

Publicado por Cambridge University Press, 2006

ISBN 10: 0521851556 ISBN 13: 9780521851558

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Dynamic Data Assimilation: A Least Squares Approach (Encyclopedia of Mathematics and its Applications, Series Number 104)

Lewis, John M.; Lakshmivarahan, S.; Dhall, Sudarshan

Publicado por Cambridge University Press, 2006

ISBN 10: 0521851556 ISBN 13: 9780521851558

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Dynamic Data Assimilation

Lewis John M. Dhall Sudarshan Lakshmivarahan S.

Publicado por Cambridge University Press, 2006

ISBN 10: 0521851556 ISBN 13: 9780521851558

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Dynamic Data Assimilation: A Least Squares Approach (Hardcover)

John M. Lewis

Publicado por Cambridge University Press, Cambridge, 2006

ISBN 10: 0521851556 ISBN 13: 9780521851558

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Hardcover. Condici�n: 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 ref. del art�culo: 9780521851558

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Dynamic Data Assimilation

Lewis, John M.|Dhall, Sudarshan|Lakshmivarahan, S.

Publicado por Cambridge University Press, 2008

ISBN 10: 0521851556 ISBN 13: 9780521851558

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Condici�n: 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 ref. del art�culo: 446950525

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Dynamic Data Assimilation: A Least Squares Approach

John M. Lewis/ S. Lakshmivarahan/ Sudarshan Dhall

Publicado por Cambridge Univ Pr, 2006

ISBN 10: 0521851556 ISBN 13: 9780521851558

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Hardcover. Condici�n: Brand New. 654 pages. 9.00x6.50x1.50 inches. In Stock. This item is printed on demand. N� de ref. del art�culo: __0521851556

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Dynamic Data Assimilation: A Least Squares Approach (Encyclopedia of Mathematics and its Applications, Series Number 104)

Lewis, John M.; Lakshmivarahan, S.; Dhall, Sudarshan

Publicado por Cambridge University Press, 2006

ISBN 10: 0521851556 ISBN 13: 9780521851558

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Dynamic Data Assimilation

John M. Lewis Sudarshan Dhall S. Lakshmivarahan

Publicado por Cambridge University Press CUP, 2006

ISBN 10: 0521851556 ISBN 13: 9780521851558

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Condici�n: New. pp. 680, Map, Index. N� de ref. del art�culo: 26516600

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Dynamic Data Assimilation: A Least Squares Approach (Hardcover)

John M. Lewis

Publicado por Cambridge University Press, Cambridge, 2006

ISBN 10: 0521851556 ISBN 13: 9780521851558

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Hardcover. Condici�n: 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 ref. del art�culo: 9780521851558

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