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<h3 class="section">16.5 Overview of real data FFTs</h3>

<p><a name="index-FFT-of-real-data-1493"></a>The functions for real data are similar to those for complex data. 
However, there is an important difference between forward and inverse
transforms.  The fourier transform of a real sequence is not real.  It is
a complex sequence with a special symmetry:

<pre class="example">     z_k = z_{n-k}^*
</pre>
   <p class="noindent">A sequence with this symmetry is called <dfn>conjugate-complex</dfn> or
<dfn>half-complex</dfn>.  This different structure requires different
storage layouts for the forward transform (from real to half-complex)
and inverse transform (from half-complex back to real).  As a
consequence the routines are divided into two sets: functions in
<code>gsl_fft_real</code> which operate on real sequences and functions in
<code>gsl_fft_halfcomplex</code> which operate on half-complex sequences.

   <p>Functions in <code>gsl_fft_real</code> compute the frequency coefficients of a
real sequence.  The half-complex coefficients c of a real sequence
x are given by fourier analysis,

<pre class="example">     c_k = \sum_{j=0}^{n-1} x_j \exp(-2 \pi i j k /n)
</pre>
   <p class="noindent">Functions in <code>gsl_fft_halfcomplex</code> compute inverse or backwards
transforms.  They reconstruct real sequences by fourier synthesis from
their half-complex frequency coefficients, c,

<pre class="example">     x_j = {1 \over n} \sum_{k=0}^{n-1} c_k \exp(2 \pi i j k /n)
</pre>
   <p class="noindent">The symmetry of the half-complex sequence implies that only half of the
complex numbers in the output need to be stored.  The remaining half can
be reconstructed using the half-complex symmetry condition. This works
for all lengths, even and odd&mdash;when the length is even the middle value
where k=n/2 is also real.  Thus only <var>n</var> real numbers are
required to store the half-complex sequence, and the transform of a real
sequence can be stored in the same size array as the original data.

   <p>The precise storage arrangements depend on the algorithm, and are
different for radix-2 and mixed-radix routines.  The radix-2 function
operates in-place, which constrains the locations where each element can
be stored.  The restriction forces real and imaginary parts to be stored
far apart.  The mixed-radix algorithm does not have this restriction, and
it stores the real and imaginary parts of a given term in neighboring
locations (which is desirable for better locality of memory accesses).

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