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Paperback. Condition: Very Good. Ex-library paperback in very nice condition with the usual markings and attachments. Text block clean and unmarked. Tight binding.
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Theoretical Computer Science: Exploring New Frontiers of Theoretical Informatics; Intermational Conference IFIP TCS 2000 Sendai, Japan, August 17-19, 2000 Proceedings
Published by Springer Verlag, New York, 2000
ISBN 10: 3540678239 ISBN 13: 9783540678236
Language: English
Hardcover. Condition: Very Good. No Jacket. Hardcover 2000 library bound edition. Ex-library book with stamps and labels attached. Binding firm. Pages unmarked and clean. Covers and text in very good condition. Series: Lecture Notes in Computer Science ;1872. [xv, 630 p. : ill. ; 24 cm].
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Data Assimilation Fundamentals
Published by Springer Nature Switzerland AG, CH, 2023
ISBN 10: 3030967115 ISBN 13: 9783030967116
Language: English
Seller: Rarewaves.com USA, London, LONDO, United Kingdom
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US$ 37.69
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Add to basketPaperback. Condition: New. 2022 ed. 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's top-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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Condition: New. 1st ed. 2022 edition NO-PA16APR2015-KAP.
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Data Assimilation Fundamentals: A Unified Formulation of the State and Parameter Estimation Problem (Springer Textbooks in Earth Sciences, Geography and Environment)
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Condition: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.
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Add to basketHardcover. Condition: Brand New. 264 pages. 9.25x6.10x0.75 inches. In Stock.
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Nonlinear Data Assimilation
Published by Springer International Publishing, 2015
ISBN 10: 331918346X ISBN 13: 9783319183466
Language: English
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Add to basketTaschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book contains two review articles on nonlinear data assimilation that deal with closely related topics but were written and can be read independently. Both contributions focus on so-called particle filters.The first contribution by Jan van Leeuwen focuses on the potential of proposal densities. It discusses the issues with present-day particle filters and explorers new ideas for proposal densities to solve them, converging to particle filters that work well in systems of any dimension, closing the contribution with a high-dimensional example. The second contribution by Cheng and Reich discusses a unified framework for ensemble-transform particle filters. This allows one to bridge successful ensemble Kalman filters with fully nonlinear particle filters, and allows a proper introduction of localization in particle filters, which has been lacking up to now.
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The Challenges of Water Management and Governance in Cities
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Add to basketPaperback. Condition: Brand New. 264 pages. 9.25x6.10x0.56 inches. In Stock.
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Add to basketPaperback. Condition: Brand New. 118 pages. 8.90x6.10x0.40 inches. In Stock.
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Nonlinear Data Assimilation
Published by Springer International Publishing, Springer International Publishing Jul 2015, 2015
ISBN 10: 331918346X ISBN 13: 9783319183466
Language: English
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Add to basketTaschenbuch. Condition: Neu. Neuware -This book contains two review articles on nonlinear data assimilation that deal with closely related topics but were written and can be read independently. Both contributions focus on so-called particle filters.The first contribution by Jan van Leeuwen focuses on the potential of proposal densities. It discusses the issues with present-day particle filters and explorers new ideas for proposal densities to solve them, converging to particle filters that work well in systems of any dimension, closing the contribution with a high-dimensional example. The second contribution by Cheng and Reich discusses a unified framework for ensemble-transform particle filters. This allows one to bridge successful ensemble Kalman filters with fully nonlinear particle filters, and allows a proper introduction of localization in particle filters, which has been lacking up to now.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 132 pp. Englisch.
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Data Assimilation Fundamentals
Published by Springer Nature Switzerland AG, CH, 2023
ISBN 10: 3030967115 ISBN 13: 9783030967116
Language: English
US$ 35.06
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Add to basketPaperback. Condition: New. 2022 ed. 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's top-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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Condition: New. pp. 314.
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Add to basketCondition: Sehr gut. Zustand: Sehr gut | Seiten: 314 | Sprache: Englisch | Produktart: Bücher.
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Theoretical Computer Science: Exploring New Frontiers of Theoretical Informatics
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Theoretical Computer Science : Exploring New Frontiers of Theoretical Information : Intermational Conference Ifip Tcs 2000 Sendai, Japan, August 17-19, 2000 Proceedings
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