Name
Abstract | ||
|---|---|---|
In this paper, quasi-interpolation based on compactly supported radial basis functions (CSRBFs) is presented for more accurate and efficient data fitting compared with global RBFs. Firstly, a CSRBF-based quasi-interpolator is constructed considering only the positions of the given data and their values. Then we make use of the first derivatives to propose a new quasi-interpolator which can achieve higher approximate order and better shape-preserving. Numerical examples demonstrate that the proposed CSRBF-based quasi-interpolation schemes are valid. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1109/CADGRAPHICS.2015.30 | 2015 14th International Conference on Computer-Aided Design and Computer Graphics (CAD/Graphics) |
Keywords | Field | DocType |
Compactly supported radial basis functions,Quasi-interpolation,First derivative,Data fitting | Computer vision,Curve fitting,Computer science,Interpolation,Algorithm,Artificial intelligence | Conference |
Citations | PageRank | References |
0 | 0.34 | 16 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Shengjun Liu | 1 | 116 | 13.79 |
| Cai Yang | 2 | 0 | 0.34 |
| Xinru Liu | 3 | 7 | 3.81 |
| Ji-An Duan | 4 | 11 | 4.04 |