Chris@19: Chris@19: Chris@19: The 1d Discrete Fourier Transform (DFT) - FFTW 3.3.4 Chris@19: Chris@19: Chris@19: Chris@19: Chris@19: Chris@19: Chris@19: Chris@19: Chris@19: Chris@19: Chris@19: Chris@19: Chris@19: Chris@19:
Chris@19: Chris@19: Chris@19:

Chris@19: Next: , Chris@19: Previous: What FFTW Really Computes, Chris@19: Up: What FFTW Really Computes Chris@19:


Chris@19:
Chris@19: Chris@19:

4.8.1 The 1d Discrete Fourier Transform (DFT)

Chris@19: Chris@19:

The forward (FFTW_FORWARD) discrete Fourier transform (DFT) of a Chris@19: 1d complex array X of size n computes an array Y, Chris@19: where: Chris@19:

.
The backward (FFTW_BACKWARD) DFT computes: Chris@19:
.
Chris@19: Chris@19:

FFTW computes an unnormalized transform, in that there is no coefficient Chris@19: in front of the summation in the DFT. In other words, applying the Chris@19: forward and then the backward transform will multiply the input by Chris@19: n. Chris@19: Chris@19:

From above, an FFTW_FORWARD transform corresponds to a sign of Chris@19: -1 in the exponent of the DFT. Note also that we use the Chris@19: standard “in-order” output ordering—the k-th output Chris@19: corresponds to the frequency k/n (or k/T, where T Chris@19: is your total sampling period). For those who like to think in terms of Chris@19: positive and negative frequencies, this means that the positive Chris@19: frequencies are stored in the first half of the output and the negative Chris@19: frequencies are stored in backwards order in the second half of the Chris@19: output. (The frequency -k/n is the same as the frequency Chris@19: (n-k)/n.) Chris@19: Chris@19: Chris@19: Chris@19: