sfft is a library to compute discrete Fourier transforms of signals with
a sparse frequency domain, using an algorithm that is more efficient than
other known FFT algorithms. It was developed by Haitham Hassanieh, Piotr
Indyk, Dina Katabi, and Eric Price at the Computer Science and Artifical
Intelligence Lab at MIT. Performance optimizations were developed by J.
Schumacher at the Computer Science Department of ETH Zurich in 2013.

WWW: http://spiral.net/software/sfft.html