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Title:
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A NEW RADIAL BASIS FUNCTION APPROXIMATION WITH REPRODUCTION |
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Author(s):
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Zuzana Majdisova, Vaclav Skala |
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ISBN:
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978-989-8533-52-4 |
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Editors:
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Katherine Blashki and Yingcai Xiao |
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Year:
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2016 |
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Edition:
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Single |
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Keywords:
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Radial basis function; RBF; approximation; optimization problem; linear reproduction |
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Type:
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Full Paper |
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First Page:
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215 |
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Last Page:
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222 |
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Language:
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English |
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Cover:
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Full Contents:
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click to dowload 
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Paper Abstract:
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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. |
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