## Alternatives to the Discrete Fourier Transform

author: Markus Püschel, Carnegie Mellon University
author: Jonathan Gross, Carnegie Mellon University
author: Aliaksei Sandryhaila, Carnegie Mellon University
author: Doru Balcan, Carnegie Mellon University
published: Dec. 20, 2008,   recorded: December 2008,   views: 1593
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# Slides

0:00 Slides Alternatives to the DFT Introduction Introduction (2) Alternatives to DFT Algebraic Signal Processing Theory (1) Algebraic Signal Processing Theory (2) Algebraic Signal Processing Theory (3) Alternative DFTs Main Theorem Theorem (Beraha-Kahane-Weiss '78) (1) Theorem (Beraha-Kahane-Weiss '78) (2) How to apply BKW? Examples and experiments (1) Examples and experiments (2) Magnitude of Fourier transform Summary References Questions - Questions

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# Description

It is well-known that the discrete Fourier transform (DFT) of a finite length discrete-time signal samples the discrete-time Fourier transform of the same signal at equidistant points on the unit circle. Hence, as the signal length goes to infinity, the DFT approaches the DTFT. Associated with the DFT are circular convolution and a periodic signal extension. In this paper we identify a large class of alternatives to the DFT using the theory of polynomial algebras. Each of these Fourier transforms approaches the DTFT just as the DFT does, but has its own signal extension and notion of convolution, which therefore are not periodic. Furthermore, these Fourier transforms have Vandermonde structure, which enables their computation via fast \$O(n \log^2(n))\$ algorithms.