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2. Fast Fourier transforms
For a full description of the FFT see, for example Ref. [5]. We consider a vector of length with elements
where . The elements of the discrete Fourier transform
(DFT) of this vector, , may then be defined by
|
(1) |
where is one of the
roots of unity
. The definition in Eq. 1
is simply a premultiplication of the vector with elements by a
matrix with elements
, and this
multiplication requires operations.
Consider the following result, known as the Danielson-Lanczos
lemma [6], applied to Eq. 1 for even :
in which we use the result
and
introduce the notation
and
to represent the even and odd elements
respectively. Equation 2 shows that a DFT of length may be
rewritten as the combination of two DFTs of length . This lemma
may be applied recursively, as long as the length of the DFT remains
even, so that if is a power of 2, it may be applied until the
trivial DFT of a vector of length 1 is required. In this case, the DFT
requires only operations, and this is the (radix-2)
FFT. The lemma may be generalised to apply when contains factors
other than 2.
In three dimensions, the definition of the DFT is
|
(3) |
Equation 3 demonstrates that the three-dimensional DFT is the
product of 3 one-dimensional DFTs which all commute with each other
since they act indepedently.
Next: 3. Traditional parallel implementation
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Previous: 1. Introduction
Peter Haynes