Accelerating the Nonuniform Fast Fourier Transform
By Leslie Greengard, June-Yub Lee. SIAM Review, 2004
776 citations recorded by the source corpus.
Subfields: Nuclear and High Energy Physics, Radiology, Nuclear Medicine and Imaging
View Paper: https://www.semanticscholar.org/paper/774fb9d4934cfcbb2ed5d2b20d7b85735aed0e6a
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In Nuclear and High Energy Physics
In Radiology, Nuclear Medicine and Imaging
- Daniel Potts
- Jens Keiner
- Stefan Kunis
- John M. Pauly
- G. Em Karniadakis
- Paris Perdikaris
- Daniele Venturi
- Dina Katabi
Citations in the corpus
- Fast geometric learning with symbolic matrices (2020, neutral): “Alternatively, semi-Eulerian methods rely on intermediate grid representations to leverage fast Fourier transforms or convolution routines [32, 51, 76].”
- Decimeter-Level Localization with a Single WiFi Access Point (2016, background): “The NDFT is an under-determined system, where the responses of multiple frequency elements are unavailable [19] [15].”
- Using NFFT 3---A Software Library for Various Nonequispaced Fast Fourier Transforms (2009, background): “Two useful properties of the Gaussian window function (C.1) that can be exploited within the presented framework have recently been reviewed in [ Greengard and Lee 2004 ].”
- Fast Direct Methods for Gaussian Processes (2014, methodology): “As mentioned in the introduction, analysis-based fast algorithms can also be used for specific kernels [15] or treated using the more general “black-box” or “kernelindependent” fast multipole methods [17], [21], [55].”
- Multifidelity Information Fusion Algorithms for High-Dimensional Systems and Massive Data sets (2016, methodology): “The Fourier coefficients ŵ(ξ) can be efficiently computed with O(Nt logNt) cost using the fast Fourier transform for regularly spaced samples or the nonuniform fast Fourier transform [23] for irregularly spaced samples.”
- Rapid gridding reconstruction with a minimal oversampling ratio (2005, background): “kernel can be quite efficient; in one dimension, the Gaussian kernel requires two exponential evaluations per data sample point plus two multiplications for each point on the grid to which this data sample is deposited [12].”