Least squares scattered data fitting by truncated SVDs

  • Authors:
  • V. Pereyra;G. Scherer

  • Affiliations:
  • Weidlinger Associates, 4410 El Camino Real, #110, Los Altos, CA;5 Wheatsheaf Close, Horsham, West Sussex, RH 12574, UK

  • Venue:
  • Applied Numerical Mathematics - Applied and computational mathematics: Selected papers of the third panamerican workshop Trujillo, Peru, 24-28 April 2000
  • Year:
  • 2002

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Abstract

The l2 fitting of scattered data by tensor products of B-splines in two and three dimensions is considered. A truncated Singular Value decomposition approach is used to automatically account for singularity and ill-conditioning of the Grammian matrix. The method does not require re-gridding and can be applied to data with large holes and irregular footprint, provided that the domain of evaluation is limited to the region where there is enough data. A direct and two iterative methods are discussed and numerical results are offered for several test data sets.