1976
DOI: 10.1073/pnas.73.4.1005
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On computing the Discrete Fourier Transform

Abstract: New algorithms for computing the Discrete Fourier Transform of n points are described. For n in the range of a few tens to a few thousands these algorithms use substantially fewer multiplications than the best algorithm previously known, and about the same number of additions.Computing the Discrete Fourier Transform (DFT) of n points:n-1 2vt Aj = wiiai, j ... .,n -1, w= e[1] =_0 has many applications in scientific and engineering calculation. In 1965 Cooley and Tukey (1) described an algorithm for computing DF… Show more

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Cited by 301 publications
(196 citation statements)
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“…Consequently, the memory requirements do not increase while performing an FFT. Other FFTs like the Winograd FFT [84] do not have this property and require more and more memory space.…”
Section: Fast Fourier Transformmentioning
confidence: 99%
“…Consequently, the memory requirements do not increase while performing an FFT. Other FFTs like the Winograd FFT [84] do not have this property and require more and more memory space.…”
Section: Fast Fourier Transformmentioning
confidence: 99%
“…New techniques were developed for the construction of large scale FF1 processors which are geared toward the use of VLSI. These techniques employ the traditional Cooley-Tukey version of the FFT [4] as well as the prime-factor a.gorithm of Good [5] and elements of the Winograd Fourier Transform [6].…”
Section: Vli Mplementation Of Digital Fourier Tranaformsmentioning
confidence: 99%
“…Winograd Fourier Transform (WFT) [1] algorithm is highly preferable in designs that involves Discrete Fourier Transform (DFT). Twiddle factor multiplication is not required for WFT, which in turn reduces the number of real multipliers needed.…”
Section: Introductionmentioning
confidence: 99%