Verlag: Cambridge University Press (edition 1), 2023
ISBN 10: 1009414291 ISBN 13: 9781009414296
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Verlag: Cambridge University Press, 2023
ISBN 10: 1009414291 ISBN 13: 9781009414296
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ISBN 10: 1009414291 ISBN 13: 9781009414296
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Verlag: Cambridge University Press, 2023
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ISBN 10: 1009414321 ISBN 13: 9781009414326
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Verlag: Cambridge University Press Aug 2023, 2023
ISBN 10: 1009414291 ISBN 13: 9781009414296
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Taschenbuch. Zustand: Neu. Neuware - This concise introduction provides an entry point to the world of inverse problems and data assimilation for advanced undergraduates and beginning graduate students in the mathematical sciences. It will also appeal to researchers in science and engineering who are interested in the systematic underpinnings of methodologies widely used in their disciplines. The authors examine inverse problems and data assimilation in turn, before exploring the use of data assimilation methods to solve generic inverse problems by introducing an artificial algorithmic time. Topics covered include maximum a posteriori estimation, (stochastic) gradient descent, variational Bayes, Monte Carlo, importance sampling and Markov chain Monte Carlo for inverse problems; and 3DVAR, 4DVAR, extended and ensemble Kalman filters, and particle filters for data assimilation. The book contains a wealth of examples and exercises, and can be used to accompany courses as well as for self-study.
Verlag: Cambridge University Press, 2023
ISBN 10: 1009414291 ISBN 13: 9781009414296
Sprache: Englisch
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Taschenbuch. Zustand: Neu. Inverse Problems and Data Assimilation | Daniel Sanz-Alonso (u. a.) | Taschenbuch | Englisch | 2023 | Cambridge University Press | EAN 9781009414296 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu.
Verlag: Cambridge University Press, 2023
ISBN 10: 1009414321 ISBN 13: 9781009414326
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Buch. Zustand: Neu. Neuware - This concise introduction provides an entry point to the world of inverse problems and data assimilation for advanced undergraduates and beginning graduate students in the mathematical sciences. It will also appeal to researchers in science and engineering who are interested in the systematic underpinnings of methodologies widely used in their disciplines. The authors examine inverse problems and data assimilation in turn, before exploring the use of data assimilation methods to solve generic inverse problems by introducing an artificial algorithmic time. Topics covered include maximum a posteriori estimation, (stochastic) gradient descent, variational Bayes, Monte Carlo, importance sampling and Markov chain Monte Carlo for inverse problems; and 3DVAR, 4DVAR, extended and ensemble Kalman filters, and particle filters for data assimilation. The book contains a wealth of examples and exercises, and can be used to accompany courses as well as for self-study.
Verlag: Cambridge University Press, 2023
ISBN 10: 1009414291 ISBN 13: 9781009414296
Sprache: Englisch
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In den WarenkorbPaperback. Zustand: Brand New. 221 pages. 8.98x5.87x0.51 inches. In Stock. This item is printed on demand.
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ISBN 10: 1009414321 ISBN 13: 9781009414326
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Hardcover. Zustand: new. Hardcover. This concise introduction provides an entry point to the world of inverse problems and data assimilation for advanced undergraduates and beginning graduate students in the mathematical sciences. It will also appeal to researchers in science and engineering who are interested in the systematic underpinnings of methodologies widely used in their disciplines. The authors examine inverse problems and data assimilation in turn, before exploring the use of data assimilation methods to solve generic inverse problems by introducing an artificial algorithmic time. Topics covered include maximum a posteriori estimation, (stochastic) gradient descent, variational Bayes, Monte Carlo, importance sampling and Markov chain Monte Carlo for inverse problems; and 3DVAR, 4DVAR, extended and ensemble Kalman filters, and particle filters for data assimilation. The book contains a wealth of examples and exercises, and can be used to accompany courses as well as for self-study. This concise introduction covers inverse problems and data assimilation, before exploring their inter-relations. Suitable for both classroom teaching and self-guided study, it is aimed at advanced undergraduates and beginning graduate students in mathematical sciences, together with researchers in science and engineering. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Verlag: Cambridge University Press, 2023
ISBN 10: 1009414321 ISBN 13: 9781009414326
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ISBN 10: 1009414321 ISBN 13: 9781009414326
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In den WarenkorbHardcover. Zustand: new. Hardcover. This concise introduction provides an entry point to the world of inverse problems and data assimilation for advanced undergraduates and beginning graduate students in the mathematical sciences. It will also appeal to researchers in science and engineering who are interested in the systematic underpinnings of methodologies widely used in their disciplines. The authors examine inverse problems and data assimilation in turn, before exploring the use of data assimilation methods to solve generic inverse problems by introducing an artificial algorithmic time. Topics covered include maximum a posteriori estimation, (stochastic) gradient descent, variational Bayes, Monte Carlo, importance sampling and Markov chain Monte Carlo for inverse problems; and 3DVAR, 4DVAR, extended and ensemble Kalman filters, and particle filters for data assimilation. The book contains a wealth of examples and exercises, and can be used to accompany courses as well as for self-study. This concise introduction covers inverse problems and data assimilation, before exploring their inter-relations. Suitable for both classroom teaching and self-guided study, it is aimed at advanced undergraduates and beginning graduate students in mathematical sciences, together with researchers in science and engineering. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.