Abstract
This paper is concerned with the approximation of discrete data using univariate B-splines. Specifically, we focus on the need to locate spline knots optimally in order to improve the fidelity of the B-Spline model to the data. It is well understood that knot placement can have a significant effect on the quality of a spline approximant. However optimizing with respect to the number and placement of knots is generally difficult. In this paper, we describe an approach in which the density of knots is controlled by a knot density function depending on a small number of parameters. Optimizing with respect to these additional parameters is straightforward and can lead to significant improvements in the approximating spline.
Original language | English |
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Title of host publication | Algorithms for Approximation |
Subtitle of host publication | Proceedings of the 5th International Conference, Chester, July 2005 |
Editors | Armin Iske, Jeremy Levesley |
Place of Publication | Berlin |
Publisher | Springer |
Pages | 249-258 |
Number of pages | 10 |
Edition | 1st |
ISBN (Electronic) | 9783540465515 |
ISBN (Print) | 9783540332831, 9783642069949 |
DOIs | |
Publication status | Published - 2007 |
Event | 5th International Conference on Algorithms for Approximation - Chester, United Kingdom Duration: 17 Jul 2005 → 21 Jul 2005 Conference number: 5 |
Conference
Conference | 5th International Conference on Algorithms for Approximation |
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Country/Territory | United Kingdom |
City | Chester |
Period | 17/07/05 → 21/07/05 |