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Computational methods for data evaluation and assimilation / / Dan Gabriel Cacuci, Ionel Michael Navon, Mihaela Ionescu-Bujor



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Autore: Cacuci D. G Visualizza persona
Titolo: Computational methods for data evaluation and assimilation / / Dan Gabriel Cacuci, Ionel Michael Navon, Mihaela Ionescu-Bujor Visualizza cluster
Pubblicazione: Boca Raton, : CRC Press, 2014
Edizione: 1st ed.
Descrizione fisica: 1 online resource (372 p.)
Disciplina: 518.0285
519.538
Soggetto topico: Mathematical analysis - Data processing
Classificazione: MAT003000
Altri autori: NavonIonel Michael  
Ionescu-BujorMihaela  
Note generali: "A Chapman & Hall book."
Nota di bibliografia: Includes bibliographical references.
Nota di contenuto: Front Cover; Contributors; Preface; List of Figures; List of Tables; Contents; Introduction; Chapter 1 - Experimental Data Evaluation: Basic Concepts; Chapter 2 - Computation of Means and Variances from Measurements; Chapter 3 - Optimization Methods For Large-Scale Data Assimilation; Chapter 4 - Basic Principles of 4-D VAR; Chapter 5 - 4-D VAR in Numerical Weather Prediction Models; Chapter 6 - Appendix A; Chapter 7 - Appendix B; Chapter 8 - Appendix C; Bibliography; Back Cover
Sommario/riassunto: Data evaluation and data combination require the use of a wide range of probability theory concepts and tools, from deductive statistics mainly concerning frequencies and sample tallies to inductive inference for assimilating non-frequency data and a priori knowledge. Computational Methods for Data Evaluation and Assimilation presents interdisciplinary methods for integrating experimental and computational information. This self-contained book shows how the methods can be applied in many scientific and engineering areas. After presenting the fundamentals underlying the evaluation of experiment
Titolo autorizzato: Computational methods for data evaluation and assimilation  Visualizza cluster
ISBN: 0-429-13654-4
1-58488-735-4
Formato: Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione: Inglese
Record Nr.: 9910826522003321
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