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  3. Multivariate Approximation
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    • Publisher:
      Cambridge University Press
      Publication date:
      06 July 2018
      19 July 2018
      ISBN:
      9781108689687
      9781108428750
      DOI:
      https://doi.org/10.1017/9781108689687
      Dimensions:
      (247 x 174 mm)
      Weight & Pages:
      1.12kg, 550 Pages
      Dimensions:
      Weight & Pages:
      • Subjects:
      Mathematics, Computational Science, Computer Science, Computer Graphics, Image Processing and Robotics, Numerical Analysis and Computational Science
      Series:
      Cambridge Monographs on Applied and Computational Mathematics (32)
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    Subjects:
    Mathematics, Computational Science, Computer Science, Computer Graphics, Image Processing and Robotics, Numerical Analysis and Computational Science
    Series:
    Cambridge Monographs on Applied and Computational Mathematics (32)
    Information

    Book description

    This self-contained, systematic treatment of multivariate approximation begins with classical linear approximation, and moves on to contemporary nonlinear approximation. It covers substantial new developments in the linear approximation theory of classes with mixed smoothness, and shows how it is directly related to deep problems in other areas of mathematics. For example, numerical integration of these classes is closely related to discrepancy theory and to nonlinear approximation with respect to special redundant dictionaries, and estimates of the entropy numbers of classes with mixed smoothness are closely related to (in some cases equivalent to) the Small Ball Problem from probability theory. The useful background material included in the book makes it accessible to graduate students. Researchers will find that the many open problems in the theory outlined in the book provide helpful directions and guidance for their own research in this exciting and active area.

    Reviews

    'This excellent book covers a variety of topics in univariate and multivariate approximation as well as their connection to computational mathematics … The exposition is designed in such a way that the reader is familiarized with the univariate results first and then the transition to the multivariate case is performed, highlighting the challenges and the new methods. The book is self-contained and is accessible to readers with graduate and advanced undergraduate background.'

    Andriy V. Prymak Source: MathSciNet

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    Contents

    Contents
    • Chapter 1 - Approximation of Univariate Functions
      pp 1-35
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