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Edité par Springer International Publishing, 2023
ISBN 10 : 3030967115 ISBN 13 : 9783030967116
Langue: anglais
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Ajouter au panierTaschenbuch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - This open-access textbook's significant contribution is the unified derivation of data-assimilation techniques from a common fundamental and optimal starting point, namely Bayes' theorem. Unique for this book is the 'top-down' derivation of the assimilation methods. It starts from Bayes theorem and gradually introduces the assumptions and approximations needed to arrive at today's popular data-assimilation methods. This strategy is the opposite of most textbooks and reviews on data assimilation that typically take a bottom-up approach to derive a particular assimilation method. E.g., the derivation of the Kalman Filter from control theory and the derivation of the ensemble Kalman Filter as a low-rank approximation of the standard Kalman Filter. The bottom-up approach derives the assimilation methods from different mathematical principles, making it difficult to compare them. Thus, it is unclear which assumptions are made to derive an assimilation method and sometimes even which problem it aspires to solve.The book'stop-down approach allows categorizing data-assimilation methods based on the approximations used. This approach enables the user to choose the most suitable method for a particular problem or application. Have you ever wondered about the difference between the ensemble 4DVar and the 'ensemble randomized likelihood' (EnRML) methods Do you know the differences between the ensemble smoother and the ensemble-Kalman smoother Would you like to understand how a particle flow is related to a particle filter In this book, we will provide clear answers to several such questions.The book provides the basis for an advanced course in data assimilation. It focuses on the unified derivation of the methods and illustrates their properties on multiple examples.It is suitable for graduate students, post-docs, scientists, and practitioners working in data assimilation.
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Ajouter au panierPaperback or Softback. Etat : New. Data Assimilation Fundamentals: A Unified Formulation of the State and Parameter Estimation Problem 0.84. Book.
Vendeur : Revaluation Books, Exeter, Royaume-Uni
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Ajouter au panierHardcover. Etat : Brand New. 264 pages. 9.25x6.10x0.75 inches. In Stock.
Edité par Springer International Publishing, Springer Nature Switzerland, 2022
ISBN 10 : 3030967085 ISBN 13 : 9783030967086
Langue: anglais
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EUR 53,49
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Ajouter au panierBuch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - This open-access textbook's significant contribution is the unified derivation of data-assimilation techniques from a common fundamental and optimal starting point, namely Bayes' theorem. Unique for this book is the 'top-down' derivation of the assimilation methods. It starts from Bayes theorem and gradually introduces the assumptions and approximations needed to arrive at today's popular data-assimilation methods. This strategy is the opposite of most textbooks and reviews on data assimilation that typically take a bottom-up approach to derive a particular assimilation method. E.g., the derivation of the Kalman Filter from control theory and the derivation of the ensemble Kalman Filter as a low-rank approximation of the standard Kalman Filter. The bottom-up approach derives the assimilation methods from different mathematical principles, making it difficult to compare them. Thus, it is unclear which assumptions are made to derive an assimilation method and sometimes even which problem it aspires to solve.The book'stop-down approach allows categorizing data-assimilation methods based on the approximations used. This approach enables the user to choose the most suitable method for a particular problem or application. Have you ever wondered about the difference between the ensemble 4DVar and the 'ensemble randomized likelihood' (EnRML) methods Do you know the differences between the ensemble smoother and the ensemble-Kalman smoother Would you like to understand how a particle flow is related to a particle filter In this book, we will provide clear answers to several such questions.The book provides the basis for an advanced course in data assimilation. It focuses on the unified derivation of the methods and illustrates their properties on multiple examples.It is suitable for graduate students, post-docs, scientists, and practitioners working in data assimilation.
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Ajouter au panierPapeback. Etat : Brand New. Brand New! Fast Delivery This is an International Edition and ship within 24-48 hours. Deliver by FedEx and Dhl, & Aramex, UPS, & USPS and we do accept APO and PO BOX Addresses. Order can be delivered worldwide within 7-11 days and we do have flat rate for up to 2LB. Extra shipping charges will be requested if the Book weight is more than 5 LB. This Item May be shipped from India, United states & United Kingdom. Depending on your location and availability.
Vendeur : Revaluation Books, Exeter, Royaume-Uni
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Ajouter au panierPaperback. Etat : Brand New. 264 pages. 9.25x6.10x0.56 inches. In Stock.
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