Adaptive and local regularization for data fitting by tensor-product spline surfaces.

Autor: Merchel, Sandra, Jüttler, Bert, Mokriš, Dominik
Zdroj: Advances in Computational Mathematics; Aug2023, Vol. 49 Issue 4, p1-24, 24p
Abstrakt: We propose to employ a non-constant regularization weight function (RWF) for data fitting via least-squares tensor-product (TP) spline fitting. In the first part of the paper, we formulate the discrete and the continuous version of the problem, and we investigate the influence of the degree of the RWF — which is also chosen as a TP spline function — in the latter situation. The second part presents two methods for automatically generating non-constant RWFs in the discrete situation. These methods are shown to be particularly useful if holes or features are present in the data. [ABSTRACT FROM AUTHOR]
Databáze: Complementary Index
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