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Scattered Data Modelling Using Radial Basis Functions

  • Armin Iske
Part of the Mathematics and Visualization book series (MATHVISUAL)

Abstract

Radial basis functions provide powerful meshless methods for multivariate interpolation from scattered data in arbitrary space dimension. This tutorial first explains the basic features of radial basis function interpolation, including its optimality properties and available error estimates, before critical aspects concerning its stability are discussed. The remainder of this contribution is then devoted to related techniques in scattered data modelling other than plain interpolation. To this end, least squares approximation and multiresolution techniques are explained, and recent progress concerning scattered data filtering is reported.

Keywords

Radial Basis Function Voronoi Diagram Delaunay Triangulation Scattered Data Thin Plate Spline 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2002

Authors and Affiliations

  • Armin Iske
    • 1
  1. 1.Zentrum MathematikTechnische Universität MünchenMunichGermany

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