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Data-Driven Computational Methods
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ISBN-13:
9781108472470
Veröffentl:
2019
Einband:
HC gerader Rücken kaschiert
Erscheinungsdatum:
11.09.2019
Seiten:
172
Autor:
John Harlim
Gewicht:
489 g
Format:
250x175x14 mm
Sprache:
Englisch
Beschreibung:
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).
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.
Describes computational methods for parametric and nonparametric modeling of stochastic dynamics. Aimed at graduate students, and suitable for self-study.