Fast Fourier Transforms for Nonequispaced Data: A Tutorial
Daniel Potts, Gabriele Steidl, Manfred Tasche · Birkhäuser Boston eBooks · 2001
In this chapter we consider approximative methods for the fast computation of multivariate discrete Fourier transforms for nonequispaced data (NDFT) in the time domain and in the frequency domain. In particular we are interested in the approximation error as function of the arithmetic complexity of the algorithm. We discuss the robustness of NDFT¡ªalgorithms with respect to roundoff errors and apply NDFT algorithms for the fast computation of Bessel transforms. These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.