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On the Constrained Solution of RBF Surface Approximation

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  • Anastasia Pasioti

    (Institute of Geodesy and Geoinformation Science, Technische Universität Berlin, Kaiserin–Augusta–Allee 104–106, 10553 Berlin, Germany)

Abstract

In this contribution, a scattered data approximation problem, chosen from the literature and using the Radial Basis Function (RBF) approach, is considered for the application of point cloud modelling. Three solutions are investigated for the approximation problem. First, a technique known from the literature is investigated using a linear combination of thin-plate splines and linear polynomials, with additional constraint equations. Then, using the same approximation function as before, a technique is developed for a rigorous consideration of the constraint equations. Finally, a technique is presented in which the approximation function consists only of a linear combination of thin-plate splines, without the introduction of linear polynomials and constraint equations. In addition, some interpolation problems with the RBF approach are discussed to present the differences between an interpolation with thin-plate splines only and an interpolation with thin-plate splines together with linear polynomials and constraint equations. Numerical examples are given to illustrate and discuss the solutions from the different techniques.

Suggested Citation

  • Anastasia Pasioti, 2022. "On the Constrained Solution of RBF Surface Approximation," Mathematics, MDPI, vol. 10(15), pages 1-26, July.
  • Handle: RePEc:gam:jmathe:v:10:y:2022:i:15:p:2582-:d:871183
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