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Titlebook: Data Assimilation; The Ensemble Kalman Geir Evensen Book 2009Latest edition Springer-Verlag Berlin Heidelberg 2009 Data assimilation.Ensem

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書目名稱Data Assimilation
副標(biāo)題The Ensemble Kalman
編輯Geir Evensen
視頻videohttp://file.papertrans.cn/263/262721/262721.mp4
概述Comprehensively covers both data assimilation and inverse methods.Presents the mathematical framework and derivations in a way which is common for any discipline where dynamics is merged with measurem
圖書封面Titlebook: Data Assimilation; The Ensemble Kalman  Geir Evensen Book 2009Latest edition Springer-Verlag Berlin Heidelberg 2009 Data assimilation.Ensem
描述.Data Assimilation comprehensively covers data assimilation and inverse methods, including both traditional state estimation and parameter estimation. This text and reference focuses on various popular data assimilation methods, such as weak and strong constraint variational methods and ensemble filters and smoothers. It is demonstrated how the different methods can be derived from a common theoretical basis, as well as how they differ and/or are related to each other, and which properties characterize them, using several examples...Rather than emphasize a particular discipline such as oceanography or meteorology, it presents the mathematical framework and derivations in a way which is common for any discipline where dynamics is merged with measurements. The mathematics level is modest, although it requires knowledge of basic spatial statistics, Bayesian statistics, and calculus of variations. Readers will also appreciate the introduction to the mathematical methods used and detailed derivations, which should be easy to follow, are given throughout the book. The codes used in several of the data assimilation experiments are available on a web page. In particular, this webpage conta
出版日期Book 2009Latest edition
關(guān)鍵詞Data assimilation; Ensemble Kalman Filter; Ensemble Kalman Smoother; Measure; bayesian statistics; invers
版次2
doihttps://doi.org/10.1007/978-3-642-03711-5
isbn_softcover978-3-642-42476-2
isbn_ebook978-3-642-03711-5
copyrightSpringer-Verlag Berlin Heidelberg 2009
The information of publication is updating

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on for any discipline where dynamics is merged with measurem.Data Assimilation comprehensively covers data assimilation and inverse methods, including both traditional state estimation and parameter estimation. This text and reference focuses on various popular data assimilation methods, such as wea
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Numa Markee,Olcay Sert,Silvia Kunitze formulation for the combined parameter and state estimation problem starting from Bayes’ theorem. Further, the resulting Euler–Lagrange equations are derived and we discuss some solution methods which also allow for the estimation of poorly known model parameters.
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Intercultural Teaching in the Polish Context measurements is avoided. The square root methods are intuitively very appealing but there are also some pitfalls as pointed out by . (2004) and .. (2005). See also the papers by . (2008) and .. (2008) for a revised interpretation and mathematical analysis of the square root schemes.
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