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Proceedings Paper

Modelling reduced sparse data
Author(s): Ryszard Kozera; Lyle Noakes
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Paper Abstract

In this paper we discuss the problem of fitting to an ordered collection of points in arbitary Euclidean space called reduced data. We are not given here the corresponding interpolation knots. Instead, these are estimated by new knots upon minimizing a relevant highly nonlinear optimization scheme based on natural spline interpolation. The existence of a global minimizer (i.e. the collection of interpolation knots in ascending order) is also addressed in this paper. Finally, Leap-Frog optimization tool is used to compute these knots approximating the unknown interpolation knots. This numerical scheme is subsequently compared with the Secant Method. Two illustrative examples are given.

Paper Details

Date Published: 28 September 2016
PDF: 8 pages
Proc. SPIE 10031, Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments 2016, 100314V (28 September 2016); doi: 10.1117/12.2249260
Show Author Affiliations
Ryszard Kozera, Warsaw Univ. of Life Sciences (Poland)
The Univ. of Western Australia (Australia)
Lyle Noakes, The Univ. of Western Australia (Australia)


Published in SPIE Proceedings Vol. 10031:
Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments 2016
Ryszard S. Romaniuk, Editor(s)

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