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  2. Vector-radix FFT algorithm - Wikipedia

    en.wikipedia.org/wiki/Vector-radix_FFT_algorithm

    The most common multidimensional FFT algorithm is the row-column algorithm, which means transforming the array first in one index and then in the other, see more in FFT. Then a radix-2 direct 2-D FFT has been developed, [ 2 ] and it can eliminate 25% of the multiplies as compared to the conventional row-column approach.

  3. Spectrum analyzer - Wikipedia

    en.wikipedia.org/wiki/Spectrum_analyzer

    An FFT analyzer computes a time-sequence of periodograms. FFT refers to a particular mathematical algorithm used in the process. This is commonly used in conjunction with a receiver and analog-to-digital converter. As above, the receiver reduces the center-frequency of a portion of the input signal spectrum, but the portion is not swept.

  4. Overlap–add method - Wikipedia

    en.wikipedia.org/wiki/Overlap–add_method

    When the DFT and IDFT are implemented by the FFT algorithm, the pseudocode above requires about N (log 2 (N) + 1) complex multiplications for the FFT, product of arrays, and IFFT. [ B ] Each iteration produces N-M+1 output samples, so the number of complex multiplications per output sample is about :

  5. Fourier-transform spectroscopy - Wikipedia

    en.wikipedia.org/wiki/Fourier-transform_spectroscopy

    An "interferogram" from a Fourier-transform spectrometer. This is the "raw data" which can be Fourier-transformed into an actual spectrum. The peak at the center is the ZPD position ("zero path difference"): Here, all the light passes through the interferometer because its two arms have equal length.

  6. Butterfly diagram - Wikipedia

    en.wikipedia.org/wiki/Butterfly_diagram

    Signal-flow graph connecting the inputs x (left) to the outputs y that depend on them (right) for a "butterfly" step of a radix-2 Cooley–Tukey FFT. This diagram resembles a butterfly (as in the morpho butterfly shown for comparison), hence the name, although in some countries it is also called the hourglass diagram.

  7. Finite impulse response - Wikipedia

    en.wikipedia.org/wiki/Finite_impulse_response

    The algorithm is iterative in nature. The DFT of an initial filter design is computed using the FFT algorithm (if an initial estimate is not available, h[n]=delta[n] can be used). In the Fourier domain, or DFT domain, the frequency response is corrected according to the desired specs, and the inverse DFT is then computed.

  8. Spectral leakage - Wikipedia

    en.wikipedia.org/wiki/Spectral_leakage

    The Fourier transform of a function of time, s(t), is a complex-valued function of frequency, S(f), often referred to as a frequency spectrum.Any linear time-invariant operation on s(t) produces a new spectrum of the form H(f)•S(f), which changes the relative magnitudes and/or angles of the non-zero values of S(f).

  9. Discrete Fourier transform - Wikipedia

    en.wikipedia.org/wiki/Discrete_Fourier_transform

    The procedure is sometimes referred to as zero-padding, which is a particular implementation used in conjunction with the fast Fourier transform (FFT) algorithm. The inefficiency of performing multiplications and additions with zero-valued "samples" is more than offset by the inherent efficiency of the FFT.