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Data assimilation[electronic resource] :mathematical concepts and instructive examples /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
杜威分類號:	519.5
書名/作者:	Data assimilation : mathematical concepts and instructive examples // by Rodolfo Guzzi.
作者:	Guzzi, Rodolfo.
出版者:	Cham : : Springer International Publishing :, 2016.
面頁冊數:	viii, 135 p. : : ill. (some col.), digital ;; 24 cm.
Contained By:	Springer eBooks
標題:	Mathematical statistics.
標題:	Computer simulation.
標題:	Earth sciences - Data processing.
標題:	Computer Science.
標題:	Simulation and Modeling.
標題:	Earth System Sciences.
標題:	Theoretical, Mathematical and Computational Physics.
標題:	Environmental Science and Engineering.
標題:	Water Quality/Water Pollution.
ISBN:	9783319224107
ISBN:	9783319224091
內容註:	Preface -- 1. Introduction through historical perspective -- 2. Representation of the physical system -- 3. Sequential interpolation -- 4. Advanced data assimilation methods -- 5. Applications -- A. Appendix.
摘要、提要註:	This book endeavours to give a concise contribution to understanding the data assimilation and related methodologies. The mathematical concepts and related algorithms are fully presented, especially for those facing this theme for the first time. The first chapter gives a wide overview of the data assimilation steps starting from Gauss' first methods to the most recent as those developed under the Monte Carlo methods. The second chapter treats the representation of the physical system as an ontological basis of the problem. The third chapter deals with the classical Kalman filter, while the fourth chapter deals with the advanced methods based on recursive Bayesian Estimation. A special chapter, the fifth, deals with the possible applications, from the first Lorenz model, passing trough the biology and medicine up to planetary assimilation, mainly on Mars. This book serves both teachers and college students, and other interested parties providing the algorithms and formulas to manage the data assimilation everywhere a dynamic system is present.
電子資源:	http://dx.doi.org/10.1007/978-3-319-22410-7

Data assimilation[electronic resource] :mathematical concepts and instructive examples /
Guzzi, Rodolfo.

Data assimilationmathematical concepts and instructive examples /[electronic resource] :by Rodolfo Guzzi. - Cham :Springer International Publishing :2016. - viii, 135 p. :ill. (some col.), digital ;24 cm. - SpringerBriefs in earth sciences,2191-5369. - SpringerBriefs in earth sciences..

Preface -- 1. Introduction through historical perspective -- 2. Representation of the physical system -- 3. Sequential interpolation -- 4. Advanced data assimilation methods -- 5. Applications -- A. Appendix.

This book endeavours to give a concise contribution to understanding the data assimilation and related methodologies. The mathematical concepts and related algorithms are fully presented, especially for those facing this theme for the first time. The first chapter gives a wide overview of the data assimilation steps starting from Gauss' first methods to the most recent as those developed under the Monte Carlo methods. The second chapter treats the representation of the physical system as an ontological basis of the problem. The third chapter deals with the classical Kalman filter, while the fourth chapter deals with the advanced methods based on recursive Bayesian Estimation. A special chapter, the fifth, deals with the possible applications, from the first Lorenz model, passing trough the biology and medicine up to planetary assimilation, mainly on Mars. This book serves both teachers and college students, and other interested parties providing the algorithms and formulas to manage the data assimilation everywhere a dynamic system is present.

ISBN: 9783319224107

Standard No.: 10.1007/978-3-319-22410-7doiSubjects--Topical Terms:

171875
Mathematical statistics.

LC Class. No.: QA276

Dewey Class. No.: 519.5

Data assimilation[electronic resource] :mathematical concepts and instructive examples /
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520 $a This book endeavours to give a concise contribution to understanding the data assimilation and related methodologies. The mathematical concepts and related algorithms are fully presented, especially for those facing this theme for the first time. The first chapter gives a wide overview of the data assimilation steps starting from Gauss' first methods to the most recent as those developed under the Monte Carlo methods. The second chapter treats the representation of the physical system as an ontological basis of the problem. The third chapter deals with the classical Kalman filter, while the fourth chapter deals with the advanced methods based on recursive Bayesian Estimation. A special chapter, the fifth, deals with the possible applications, from the first Lorenz model, passing trough the biology and medicine up to planetary assimilation, mainly on Mars. This book serves both teachers and college students, and other interested parties providing the algorithms and formulas to manage the data assimilation everywhere a dynamic system is present.
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