Sciweavers

MOC
1998

The approximation power of moving least-squares

14 years 8 days ago
The approximation power of moving least-squares
A general method for near-best approximations to functionals on Rd, using scattered-data information is discussed. The method is actually the moving least-squares method, presented by the Backus-Gilbert approach. It is shown that the method works very well for interpolation, smoothing and derivatives’ approximations. For the interpolation problem this approach gives Mclain’s method. The method is near-best in the sense that the local error is bounded in terms of the error of a local best polynomial approximation. The interpolation approximation in Rd is shown to be a C∞ function, and an approximation order result is proven for quasi-uniform sets of data points.
David Levin
Added 22 Dec 2010
Updated 22 Dec 2010
Type Journal
Year 1998
Where MOC
Authors David Levin
Comments (0)