Data-Driven Computational Methods: Parameter and Operator Estimations
Author:   John Harlim (Pennsylvania State University)
Publisher:   Cambridge University Press
ISBN:  

9781108472470


Pages:   168
Publication Date:   12 July 2018
Format:   Hardback
Availability:   Available To Order   Availability explained
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Data-Driven Computational Methods: Parameter and Operator Estimations


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Full Product Details

Author:   John Harlim (Pennsylvania State University)
Publisher:   Cambridge University Press
Imprint:   Cambridge University Press
Dimensions:   Width: 17.80cm , Height: 1.30cm , Length: 25.30cm
Weight:   0.500kg
ISBN:  

9781108472470


ISBN 10:   1108472478
Pages:   168
Publication Date:   12 July 2018
Audience:   College/higher education ,  Professional and scholarly ,  Postgraduate, Research & Scholarly ,  Professional & Vocational
Format:   Hardback
Publisher's Status:   Active
Availability:   Available To Order   Availability explained
We have confirmation that this item is in stock with the supplier. It will be ordered in for you and dispatched immediately.

Table of Contents

1. Introduction; 2. Markov chain Monte Carlo; 3. Ensemble Kalman filters; 4. Stochastic spectral methods; 5. Karhunen–Loève expansion; 6. Diffusion forecast; Appendix A. Elementary probability theory; Appendix B. Stochastic processes; Appendix C. Elementary differential geometry; References; Index.

Reviews

'The MATLAB code used for the examples in the book can be downloaded from the publisher's website; the scripts are short, well commented and can be understood without difficulty (even if you are not a MATLAB expert).' Fabio Mainardi, MAA Reviews 'The MATLAB code used for the examples in the book can be downloaded from the publisher's website; the scripts are short, well commented and can be understood without difficulty (even if you are not a MATLAB expert).' Fabio Mainardi, MAA Reviews


'The MATLAB code used for the examples in the book can be downloaded from the publisher's website; the scripts are short, well commented and can be understood without difficulty (even if you are not a MATLAB expert).' Fabio Mainardi, MAA Reviews


Author Information

John Harlim is a Professor of Mathematics and Meteorology at the Pennsylvania State University. His research interests include data assimilation and stochastic computational methods. In 2012, he received the Frontiers in Computational Physics award from the Journal of Computational Physics for his research contributions on computational methods for modeling Earth systems. He has previously co-authored another book, Filtering Complex Turbulent Systems (Cambridge, 2012).

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