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 * I also have this code as '''APL\11''' or '''aplc''' plain text - contact me if you need these :  J.B.W.Webber@kent.ac.uk  * I also have this code as '''APL\11''' or '''aplc''' plain text - contact me if you need these : J.B.W.Webber@kent.ac.uk
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Algorithms: Digital Signal Processing

Fast Fourier Transform

Overview

  • [Still being edited by Beau]
  • A Fourier Transform (FFT) is a method of calculating the frequency components in a data set - and the inverse FFT converts back from the frequency domain - 4 applications of the FFT rotates you round the complex plane and leaves you back with the original data.

    Wikipedia :

  • • A fast Fourier transform (FFT) is an efficient algorithm to compute the discrete Fouriertransform (DFT) and its inverse.

  • • By far the most common FFT is the Cooley-Tukey algorithm :

  • • The most well-known use of the Cooley-Tukey algorithm is to divide the transform into two pieces of size N / 2 at each step...

APLX FFT Code

This is as given in <NAME>'s article in Apl Congress 1973, p 267, with just a few comments added.

  • X and Z are two row matrixes representing the real and imaginary data.
  • Zero frequency is at Z[1;], maximum frequency in the middle; from there to ¯1↑[1] Z are negative frequencies. i.e. for an input Gaussian they transform a 'bath-tub' to a 'bath-tub'.
  •     Z←fft X;N;R;M;L;P;Q;S;T;O
    ⍝ Apl Congress 1973, p 267.
    ⍝ Restructure as an array of
    ⍝  primitive 2×2 FFT Butterflies
    X←(2,R←(M←⌊2⍟N←¯1↑⍴X)⍴2)⍴⍉X
    ⍝ Build sin and cosine table :
    Z←R⍴⍉2 1∘.○○(-(O←?1)-⍳P)÷P←N÷2
    ⍝ Z←R⍴⍉2 1∘.○○((-(O←?1)-⍳N)-P)÷P←N÷2
    Q←⍳P←M-1+L←0
    T←M-~O
    loop:→(M≤L←L+1)⍴done
    X←(+⌿X),[O+¯0.5+S←M-L](-/Z×-⌿X),[O+P-0.5]+/Z×⌽-⌿X
    Z←(((-L)⌽Q),T)⍉R⍴((1+P↑(S-1)⍴1),2)↑Z
    →loop
    done:Z←⍉(N,2)⍴(+⌿X),[O-0.5]-⌿X

Variants

  • I also have this code as APL\11 or aplc plain text - contact me if you need these : J.B.W.Webber@kent.ac.uk

  • As Lab-Tools Ltd. I can supply well-tested variants that have a time column, work with real and imaginary data, are correctly normalised in both amplitude and time, and (say) transform a centralised Gaussian to a centralised Gaussian. Also variants that transform Q to R (and R to Q) for neutron and X-Ray scattering. These have been tested with up to 100k data point (2*17) arrays : Beau@Lab-Tools.com


Algorithms: Digital Signal Processing

FastFourierTransform (last edited 2017-02-16 19:34:34 by KaiJaeger)