Dynamic Data Assimilation A Least Squares Approach

Name: Dynamic Data Assimilation A Least Squares Approach
Price: 88.07 USD
Availability: InStock
ISBN: 9780521851558

ISBN-10: 0521851556

ISBN-13: 9780521851558

Edition: 2006

Authors: Sudarshan Dhall, S. Lakshmivarahan, John M. Lewis, B. Doran, P. Flajolet

List price: $242.00

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Description:

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…

Book details

List price: $242.00
Copyright year: 2006
Publisher: Cambridge University Press
Publication date: 8/3/2006
Binding: Hardcover
Pages: 680
Size: 6.46" wide x 9.61" long x 1.54" tall
Weight: 2.420
Language: English

Sudarshan K. Dhall is a Professor at the School of Computer Science, University of Oklahoma.




Synopsis



Pathways into data assimilation: illustrative examples



Applications



Brief history of data assimilation



Linear least squares estimation: method of normal equations



A geometric view: projection and invariance



Nonlinear least squares estimation



Recursive least squares estimation



Matrix methods



Optimisation: steepest descent method



Conjugate direction/gradient methods



Newton and quasi-Newton methods



Principles of statistical estimation



Statistical least squares estimation



Maximum likelihood method



Bayesian estimation method



From Gauss to Kalman: sequential, linear minimum variance estimation



Data assimilation-static models: concepts and formulation



Classical algorithms for data assimilation



3DVAR - a Bayesian formulation



Spatial digital filters



Dynamical data assimilation: the straight line problem



First-order adjoint method: linear dynamics



First-order adjoint method: nonlinear dynamics



Second-order adjoint method



The ADVAR problem: a statistical and a recursive view



Linear filtering - Part I: Kalman filter



Linear filtering-part II



Nonlinear filtering



Reduced rank filters



Predictability: a stochastic view



Predictability: a deterministic view


Bibliography


Index