Data assimilation : a mathematical introduction

By: Kody LawContributor(s): Andrew Stuart | Konstantinos ZygalakisMaterial type: TextTextSeries: Texts in Applied Mathematics ; Vol. 62Publication details: Heidelberg: Springer, [c2015]Description: 242 pISBN: 978-3-319-36687-6Subject(s): MathematicsOnline resources: Click here to access online
Contents:
1. Mathematical Background 2. Discrete Time: Formulation 3. Discrete Time: Smoothing Algorithms 4. Discrete Time: Filtering Algorithms 5. Discrete Time: MATLAB Programs 6. Continuous Time: Formulation 7. Continuous Time: Smoothing Algorithms 8. Continuous Time: Filtering Algorithms 9. Continuous Time: MATLAB Programs
Summary: This book provides a systematic treatment of the mathematical underpinnings of work in data assimilation, covering both theoretical and computational approaches. Specifically the authors develop a unified mathematical framework in which a Bayesian formulation of the problem provides the bedrock for the derivation, development and analysis of algorithms; the many examples used in the text, together with the algorithms which are introduced and discussed, are all illustrated by the MATLAB software detailed in the book and made freely available online. --- summary provided by publisher
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Item type Current library Collection Shelving location Call number Status Notes Date due Barcode Item holds
Book Book ICTS
Mathematic Rack No 6 QA401 (Browse shelf (Opens below)) Available Billno:95020; Billdate: 2016-07-28 00268
Total holds: 0

1. Mathematical Background
2. Discrete Time: Formulation
3. Discrete Time: Smoothing Algorithms
4. Discrete Time: Filtering Algorithms
5. Discrete Time: MATLAB Programs
6. Continuous Time: Formulation
7. Continuous Time: Smoothing Algorithms
8. Continuous Time: Filtering Algorithms
9. Continuous Time: MATLAB Programs

This book provides a systematic treatment of the mathematical underpinnings of work in data assimilation, covering both theoretical and computational approaches. Specifically the authors develop a unified mathematical framework in which a Bayesian formulation of the problem provides the bedrock for the derivation, development and analysis of algorithms; the many examples used in the text, together with the algorithms which are introduced and discussed, are all illustrated by the MATLAB software detailed in the book and made freely available online. --- summary provided by publisher

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