Radial functions are a powerful tool in many areas of multi-dimensional
approximation, especially when dealing with scattered data.
We present a fast approximate algorithm for the evaluation of linear
combinations of radial functions on the sphere $\mathbb{S}^2$.
The approach is based on a particular rank approximation of the corresponding
Gram matrix and fast algorithms for spherical Fourier transforms.
The proposed method takes $\mathcal{O}(L)$ arithmetic operations for $L$
arbitrarily distributed nodes on the sphere.
In contrast to other methods, we do not require the nodes to be sorted or
pre-processed in any way, thus the pre-computation effort only depends on the
particular radial function and the desired accuracy.
We establish explicit error bounds for a range of radial functions and provide
numerical examples covering approximation quality, speed measurements, and a
comparison of our particular matrix approximation with a truncated singular
value decomposition.
Keywords:
Fast discrete summation, Radial basis
functions, Zonal functions, FFT, NFFT