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Fast linear transforms are ubiquitous in machine learning, including the discrete Fourier transform, discrete cosine transform, and other structured transformations such as convolutions. All of these transforms can be represented by dense…

Machine Learning · Computer Science 2021-01-01 Tri Dao , Albert Gu , Matthew Eichhorn , Atri Rudra , Christopher Ré

Fast Fourier transform algorithms are an arsenal of effective tools for solving various problems of analysis and high-speed processing of signals of various natures. Almost all of these algorithms are designed to process sequences of…

Data Structures and Algorithms · Computer Science 2025-04-11 Aleksandr Cariow

How could the Fourier and other transforms be naturally discovered if one didn't know how to postulate them? In the case of the Discrete Fourier Transform (DFT), we show how it arises naturally out of analysis of circulant matrices. In…

Signal Processing · Electrical Eng. & Systems 2022-04-27 Bassam Bamieh

An algorithm is presented allowing the construction of fast Fourier transforms for any solvable group on a classical computer. The special structure of the recursion formula being the core of this algorithm makes it a good starting point to…

Quantum Physics · Physics 2023-11-27 Markus Pueschel , Martin Roetteler , Thomas Beth

Finite (or Discrete) Fourier Transforms (FFT) are essential tools in engineering disciplines based on signal transmission, which is the case in most of them. FFT are related with circulant matrices, which can be viewed as group matrices of…

Number Theory · Mathematics 2013-01-08 Kanemitsu Shigeru , Waldschmidt Michel

A discrete complexified quaternion Fourier transform is introduced. This is a generalization of the discrete quaternion Fourier transform to the case where either or both of the signal/image and the transform kernel are complex…

Numerical Analysis · Mathematics 2008-03-19 Salem Said , Nicolas Le Bihan , Stephen J. Sangwine

The Fractional Fourier Transform is a ubiquitous signal processing tool in basic and applied sciences. The Fractional Fourier Transform generalizes every property and application of the Fourier Transform. Despite the practical importance of…

Signal Processing · Electrical Eng. & Systems 2020-10-21 Amir R. Nafchi , Eric Hamke , Cristina Pereyra , Ramiro Jordan

Fast Fourier Transform (FFT) is an efficient algorithm to compute the Discrete Fourier Transform (DFT) and its inverse. In this paper, we pay special attention to the description of complex-data FFT. We analyze two common descriptions of…

Numerical Analysis · Computer Science 2011-10-28 Zhengjun Cao , Xiao Fan

The Fourier transform is approximated over a finite domain using a Riemann sum. This Riemann sum is then expressed in terms of the discrete Fourier transform, which allows the sum to be computed with a fast Fourier transform algorithm more…

Numerical Analysis · Mathematics 2015-08-07 Jeremy Axelrod

The fast Fourier transform (FFT) is one of the most successful numerical algorithms of the 20th century and has found numerous applications in many branches of computational science and engineering. The FFT algorithm can be derived from a…

Numerical Analysis · Mathematics 2021-02-10 Daan Camps , Roel Van Beeumen , Chao Yang

Calculations of the Fourier transform of a constant quantity over an area or volume defined by polygons (connected vertices) are often useful in modeling wave scattering, or in fourier-space filtering of real-space vector-based volumes and…

Numerical Analysis · Mathematics 2021-04-20 Brian B. Maranville

The Arithmetic Fourier Transform is a numerical formulation for computing Fourier series and Taylor series coefficients. It competes with the Fast Fourier Transform in terms of speed and efficiency, requiring only addition operations and…

Complex Variables · Mathematics 2020-12-15 Joel L. Schiff

Fourier transforms are ubiquitous mathematical tools in basic and applied sciences. We here report classical and quantum optical realizations of the discrete fractional Fourier transform, a generalization of the Fourier transform. In the…

In calculating integral or discrete transforms, use has been made of fast algorithms for multiplying vectors by matrices whose elements are specified as values of special (Chebyshev, Legendre, Laguerre, etc.) functions. The currently…

Numerical Analysis · Mathematics 2022-08-11 Andrew V. Terekhov

For a sample set of 1024 values, the FFT is 102.4 times faster than the discrete Fourier transform (DFT). The basis for this remarkable speed advantage is the `bit-reversal' scheme of the Cooley-Tukey algorithm. Eliminating the burden of…

History and Overview · Mathematics 2007-05-23 Randall D. Peters

We introduce a fast Fourier transform on regular d-dimensional lattices. We investigate properties of congruence class representants, i.e. their ordering, to classify directions and derive a Cooley-Tukey-Algorithm. Despite the fast Fourier…

Numerical Analysis · Mathematics 2013-06-18 Ronny Bergmann

We present a general diagrammatic approach to the construction of efficient algorithms for computing the Fourier transform of a function on a finite group. By extending work which connects Bratteli diagrams to the construction of Fast…

Representation Theory · Mathematics 2015-12-09 David Maslen , Daniel N. Rockmore , Sarah Wolff

Discrete trigonometric transformations, such as the discrete Fourier and cosine/sine transforms, are important in a variety of applications due to their useful properties. For example, one well-known property is the convolution theorem for…

Information Theory · Computer Science 2015-10-05 Xing Ouyang , Cleitus Antony , Fatima Gunning , Hongyu Zhang , Yong Liang Guan

This paper introduces the theory and hardware implementation of two new algorithms for computing a single component of the discrete Fourier transform. In terms of multiplicative complexity, both algorithms are more efficient, in general,…

Discrete Mathematics · Computer Science 2018-01-24 G. Jerônimo da Silva , R. M. Campello de Souza , H. M. de Oliveira

The prevalence of convolution in applications within signal processing, deep neural networks, and numerical solvers has motivated the development of numerous fast convolution algorithms. In many of these problems, convolution is performed…

Numerical Analysis · Mathematics 2020-07-03 Caleb Ju , Edgar Solomonik
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