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Autor(en): 
  • Andrew Stuart
  • Kody Law
  • Konstantinos Zygalakis
  • Data Assimilation: A Mathematical Introduction 
     

    (Buch)
    Dieser Artikel gilt, aufgrund seiner Grösse, beim Versand als 3 Artikel!


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   Auf Bestellung (Lieferzeit unbekannt)
    Veröffentlichung:  Oktober 2016  
    Genre:  Schulbücher 
     
    B / Computational Mathematics and Numerical Analysis / Computer mathematics / Dynamical systems / Dynamical Systems and Ergodic Theory / Dynamics / Ergodic theory / Mathematics and Statistics
    ISBN:  9783319366876 
    EAN-Code: 
    9783319366876 
    Verlag:  Springer EN 
    Einband:  Kartoniert  
    Sprache:  English  
    Serie:  #62 - Texts in Applied Mathematics  
    Dimensionen:  H 254 mm / B 178 mm / D  
    Gewicht:  5533 gr 
    Seiten:  242 
    Illustration:  XVIII, 242 p. 61 illus., 41 illus. in color., farbige Illustrationen, schwarz-weiss Illustrationen 
    Zus. Info:  EUDR exemption - product or manufacturing materials placed on the market prior to 31.12.2025. 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:
    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.

    The book is organized into nine chapters: the first contains a brief introduction to the mathematical tools around which the material is organized; the next four are concerned with discrete time dynamical systems and discrete time data; the last four are concerned with continuous time dynamical systems and continuous time data and are organized analogously to the corresponding discrete time chapters.

    This book isaimed at mathematical researchers interested in a systematic development of this interdisciplinary field, and at researchers from the geosciences, and a variety of other scientific fields, who use tools from data assimilation to combine data with time-dependent models. The numerous examples and illustrations make understanding of the theoretical underpinnings of data assimilation accessible. Furthermore, the examples, exercises and MATLAB software, make the book suitable for students in applied mathema

    tics, either through a lecture course, or through self-study.   

      



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