Title:
|
A NEW RADIAL BASIS FUNCTION APPROXIMATION WITH REPRODUCTION |
Author(s):
|
Zuzana Majdisova, Vaclav Skala |
ISBN:
|
978-989-8533-52-4 |
Editors:
|
Katherine Blashki and Yingcai Xiao |
Year:
|
2016 |
Edition:
|
Single |
Keywords:
|
Radial basis function; RBF; approximation; optimization problem; linear reproduction |
Type:
|
Full Paper |
First Page:
|
215 |
Last Page:
|
222 |
Language:
|
English |
Cover:
|
|
Full Contents:
|
click to dowload
|
Paper Abstract:
|
Approximation of scattered geometric data is often a task in many engineering problems. The Radial Basis Function (RBF) approximation is appropriate for large scattered (unordered) datasets in -dimensional space. This method is useful for a higher dimension , because the other methods require a conversion of a scattered dataset to a semi-regular mesh using some tessellation techniques, which is computationally expensive. The RBF approximation is non-separable, as it is based on a distance of two points. It leads to a solution of overdetermined Linear System of Equations (LSE). In this paper a new RBF approximation method is derived and presented. The presented approach is applicable for -dimensional cases in general. |
|
|
|
|