A Radial Basis Function Approximation for Large Datasets

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F16%3A43928979" target="_blank" >RIV/49777513:23520/16:43928979 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Result language
angličtina
Original language name
A Radial Basis Function Approximation for Large Datasets
Original language description
Approximation of scattered data is often a task in many engineering problems. The Radial Basis Function (RBF) approximation is appropriate for large scattered datasets in d-dimensional space. It is non-separable approximation, as it is based on a distance between two points. This method leads to a solution of overdetermined linear system of equations. In this paper a new approach to the RBF approximation of large datasets is introduced and experimental results for different real datasets and different RBFs are presented with respect to the accuracy of computation. The proposed approach uses symmetry of matrix and partitioning matrix into blocks.
Czech name
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Czech description
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Project
<a href="/en/project/LH12181" target="_blank" >LH12181: Development of Algorithms for Computer Graphics and CAD/CAM systems</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Publication year
2016
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Proceedings of SIGRAD 2016, May 23rd and 24th, Visby, Sweden
ISBN
978-91-7685-731-1
ISSN
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e-ISSN
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Number of pages
6
Pages from-to
9-14
Publisher name
Linköping University Electronic Press
Place of publication
Visby, Sweden
Event location
Visby
Event date
May 23, 2016
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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