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    Fast Fourier transform - Wikipedia

    A Fast Fourier Transform (FFT) is an algorithm that computes the Discrete Fourier Transform (DFT) of a sequence, or its inverse (IDFT). Fourier analysis converts a signal from its original domain (often time or space) to a representation in the frequency domain and vice versa. The DFT is obtained by decomposing a … See more

    The development of fast algorithms for DFT can be traced to Carl Friedrich Gauss's unpublished 1805 work on the orbits of asteroids Pallas and Juno. Gauss wanted to interpolate the orbits from sample observations; his … See more

    Let $${\displaystyle x_{0},\ldots ,x_{n-1}}$$ be complex numbers. The DFT is defined by the formula
    $${\displaystyle X_{k}=\sum _{m=0}^{n-1}x_{m}e^{-i2\pi km/n}\qquad k=0,\ldots ,n-1,}$$
    where See more

    Bounds on complexity and operation counts
    A fundamental question of longstanding theoretical interest is … See more

    An $${\textstyle O(n^{5/2}\log n)}$$ generalization to spherical harmonics on the sphere S with n nodes was described by Mohlenkamp, along with an algorithm conjectured (but … See more

    1805
    Carl Friedrich Gauss's unpublished work on the orbits of asteroids Pallas and Juno.
    1932
    Frank Yates published his version of FFT algorithm called interaction algorithm.
    1942
    G. C. Danielson and Cornelius Lanczos published their version to compute DFT for x-ray crystallography.
    1965
    Cooley and Tukey independently rediscovered the earlier algorithms and published a more general FFT.
    1994
    Gilbert Strang described the FFT as 'the most important numerical algorithm of our lifetime'.
    2005
    Frigo and Johnson published a paper on FFT algorithms.

    Cooley–Tukey algorithm
    By far the most commonly used FFT is the Cooley–Tukey algorithm. This is a divide-and-conquer algorithm that recursively breaks down a DFT … See more

    In many applications, the input data for the DFT are purely real, in which case the outputs satisfy the symmetry
    See more

    As defined in the multidimensional DFT article, the multidimensional DFT
    transforms an array … See more

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  2. Interpret FFT results – obtaining magnitude and phase …

    WebNov 19, 2015 · 3a. Extract amplitude of frequency components (amplitude spectrum) The FFT function computes the complex DFT and the hence …

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    • Fast Fourier Transform (FFT) — Python Numerical Methods

    • People also ask
      For other uses, see FFT (disambiguation). A Fast Fourier Transform ( FFT) is an algorithm that computes the Discrete Fourier Transform (DFT) of a sequence, or its inverse (IDFT). Fourier analysis converts a signal from its original domain (often time or space) to a representation in the frequency domain and vice versa.
      This is implemented as sequence of 1- or 2-bit quantum gates now known as quantum FFT, which is effectively the Cooley–Tukey FFT realized as a particular factorization of the Fourier matrix. Extension to these ideas is currently being explored.
      An FFT rapidly computes such transformations by factorizing the DFT matrix into a product of sparse (mostly zero) factors. As a result, it manages to reduce the complexity of computing the DFT from , which arises if one simply applies the definition of DFT, to , where n is the data size.
      This method (and the general idea of an FFT) was popularized by a publication of Cooley and Tukey in 1965, but it was later discovered that those two authors had independently re-invented an algorithm known to Carl Friedrich Gauss around 1805 (and subsequently rediscovered several times in limited forms).
    • Fast Fourier Transformation for polynomial multiplication

      WebMar 15, 2023 · Fast Fourier Transform (FFT) can perform DFT and inverse DFT in time O (nlogn). DFT. DFT is evaluating values of polynomial at n complex nth roots of unity . So, for k = 0, 1, 2, …, n-1, y = (y0, y1, y2, …

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    • Plotting a fast Fourier transform in Python - Stack Overflow