sfft

Optimized Sparse Fast Fourier Transform

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.