Novel RBF Approximation Method Based on Geometrical Properties for Signal Processing

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F19%3A43958008" target="_blank" >RIV/49777513:23520/19:43958008 - isvavai.cz</a>

Výsledek na webu

<a href="http://afrodita.zcu.cz/~skala/publications.htm" target="_blank" >http://afrodita.zcu.cz/~skala/publications.htm</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/Informatics47936.2019.9119276" target="_blank" >10.1109/Informatics47936.2019.9119276</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Novel RBF Approximation Method Based on Geometrical Properties for Signal Processing

Popis výsledku v původním jazyce

Interpolation and approximation methods are widely used in many areas. They can be divided to methods based on meshing (tessellation) of the data domain and to meshless (meshfree) methods, which do not require the domain tessellation of scattered data. Scattered n-dimensional data radial basis function (RBF) interpolation and approximation leads to a solution of linear system of equations. This contribution presents a new approach to the RBF approximation based on analysis of geometrical properties of signals, i.e. sampled curves. Also a newly developed radial basis function was used and proved better precision of approximation. Experimental comparison of several RBF functions (Gauss, Thin-Plate Spline, CS-RBF and a new proposed RBF) is described with analysis of their properties. Special attention was taken to the precision of approximation and conditionality issues. The proposed approach can be extended to a higher dimensional case and for vector data, e.q. fluid flow, too.

Název v anglickém jazyce

Novel RBF Approximation Method Based on Geometrical Properties for Signal Processing

Popis výsledku anglicky

Interpolation and approximation methods are widely used in many areas. They can be divided to methods based on meshing (tessellation) of the data domain and to meshless (meshfree) methods, which do not require the domain tessellation of scattered data. Scattered n-dimensional data radial basis function (RBF) interpolation and approximation leads to a solution of linear system of equations. This contribution presents a new approach to the RBF approximation based on analysis of geometrical properties of signals, i.e. sampled curves. Also a newly developed radial basis function was used and proved better precision of approximation. Experimental comparison of several RBF functions (Gauss, Thin-Plate Spline, CS-RBF and a new proposed RBF) is described with analysis of their properties. Special attention was taken to the precision of approximation and conditionality issues. The proposed approach can be extended to a higher dimensional case and for vector data, e.q. fluid flow, too.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

<a href="/cs/project/GA17-05534S" target="_blank" >GA17-05534S: Meshless metody pro vizualizaci velkých časově-prostorových vektorových dat</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2019

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

INFORMATICS 2019

ISBN

978-1-72813-181-8

ISSN

—

e-ISSN

—

Počet stran výsledku

6

Strana od-do

451-456

Název nakladatele

IEEE

Místo vydání

Piscataway

Místo konání akce

Poprad

Datum konání akce

20. 11. 2019

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000610452900074