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  2. Split-radix FFT algorithm - Wikipedia

    en.wikipedia.org/wiki/Split-radix_FFT_algorithm

    The split-radix FFT is a fast Fourier transform (FFT) algorithm for computing the discrete Fourier transform (DFT), and was first described in an initially little-appreciated paper by R. Yavne (1968) and subsequently rediscovered simultaneously by various authors in 1984.

  3. Fast Fourier transform - Wikipedia

    en.wikipedia.org/wiki/Fast_Fourier_transform

    A fast Fourier transform (FFT) is an algorithm that computes the discrete Fourier transform (DFT) of a sequence, or its inverse (IDFT). A Fourier transform converts a signal from its original domain (often time or space) to a representation in the frequency domain and vice versa.

  4. Vector-radix FFT algorithm - Wikipedia

    en.wikipedia.org/wiki/Vector-radix_FFT_algorithm

    As with the Cooley–Tukey FFT algorithm, the two dimensional vector-radix FFT is derived by decomposing the regular 2-D DFT into sums of smaller DFT's multiplied by "twiddle" factors. A decimation-in-time ( DIT ) algorithm means the decomposition is based on time domain x {\displaystyle x} , see more in Cooley–Tukey FFT algorithm .

  5. File:Python Programming eBook Reader.pdf - Wikipedia

    en.wikipedia.org/wiki/File:Python_Programming...

    You are free: to share – to copy, distribute and transmit the work; to remix – to adapt the work; Under the following conditions: attribution – You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses ...

  6. Overlap–add method - Wikipedia

    en.wikipedia.org/wiki/Overlap–add_method

    The two methods are also compared in Figure 3, created by Matlab simulation. The contours are lines of constant ratio of the times it takes to perform both methods. When the overlap-add method is faster, the ratio exceeds 1, and ratios as high as 3 are seen. Fig 3: Gain of the overlap-add method compared to a single, large circular convolution.

  7. Goertzel algorithm - Wikipedia

    en.wikipedia.org/wiki/Goertzel_algorithm

    The Goertzel algorithm is a technique in digital signal processing (DSP) for efficient evaluation of the individual terms of the discrete Fourier transform (DFT). It is useful in certain practical applications, such as recognition of dual-tone multi-frequency signaling (DTMF) tones produced by the push buttons of the keypad of a traditional analog telephone.

  8. Cooley–Tukey FFT algorithm - Wikipedia

    en.wikipedia.org/wiki/Cooley–Tukey_FFT_algorithm

    The Cooley–Tukey algorithm, named after J. W. Cooley and John Tukey, is the most common fast Fourier transform (FFT) algorithm. It re-expresses the discrete Fourier transform (DFT) of an arbitrary composite size = in terms of N 1 smaller DFTs of sizes N 2, recursively, to reduce the computation time to O(N log N) for highly composite N (smooth numbers).

  9. Rader's FFT algorithm - Wikipedia

    en.wikipedia.org/wiki/Rader's_FFT_algorithm

    Rader's algorithm (1968), [1] named for Charles M. Rader of MIT Lincoln Laboratory, is a fast Fourier transform (FFT) algorithm that computes the discrete Fourier transform (DFT) of prime sizes by re-expressing the DFT as a cyclic convolution (the other algorithm for FFTs of prime sizes, Bluestein's algorithm, also works by rewriting the DFT as a convolution).