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author Chris Cannam <cannam@all-day-breakfast.com>
date Wed, 20 Mar 2013 15:35:50 +0000
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cannam@95 3 <title>Multi-dimensional Transforms - FFTW 3.3.3</title>
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cannam@95 48 <a name="Multi-dimensional-Transforms"></a>
cannam@95 49 <a name="Multi_002ddimensional-Transforms"></a>
cannam@95 50 <p>
cannam@95 51 Previous:&nbsp;<a rel="previous" accesskey="p" href="1d-Discrete-Hartley-Transforms-_0028DHTs_0029.html#g_t1d-Discrete-Hartley-Transforms-_0028DHTs_0029">1d Discrete Hartley Transforms (DHTs)</a>,
cannam@95 52 Up:&nbsp;<a rel="up" accesskey="u" href="What-FFTW-Really-Computes.html#What-FFTW-Really-Computes">What FFTW Really Computes</a>
cannam@95 53 <hr>
cannam@95 54 </div>
cannam@95 55
cannam@95 56 <h4 class="subsection">4.8.6 Multi-dimensional Transforms</h4>
cannam@95 57
cannam@95 58 <p>The multi-dimensional transforms of FFTW, in general, compute simply the
cannam@95 59 separable product of the given 1d transform along each dimension of the
cannam@95 60 array. Since each of these transforms is unnormalized, computing the
cannam@95 61 forward followed by the backward/inverse multi-dimensional transform
cannam@95 62 will result in the original array scaled by the product of the
cannam@95 63 normalization factors for each dimension (e.g. the product of the
cannam@95 64 dimension sizes, for a multi-dimensional DFT).
cannam@95 65
cannam@95 66 <p><a name="index-r2c-325"></a>The definition of FFTW's multi-dimensional DFT of real data (r2c)
cannam@95 67 deserves special attention. In this case, we logically compute the full
cannam@95 68 multi-dimensional DFT of the input data; since the input data are purely
cannam@95 69 real, the output data have the Hermitian symmetry and therefore only one
cannam@95 70 non-redundant half need be stored. More specifically, for an n<sub>0</sub>&nbsp;&times;&nbsp;n<sub>1</sub>&nbsp;&times;&nbsp;n<sub>2</sub>&nbsp;&times;&nbsp;&hellip;&nbsp;&times;&nbsp;n<sub>d-1</sub> multi-dimensional real-input DFT, the full (logical) complex output array
cannam@95 71 <i>Y</i>[<i>k</i><sub>0</sub>, <i>k</i><sub>1</sub>, ...,
cannam@95 72 <i>k</i><sub><i>d-1</i></sub>]has the symmetry:
cannam@95 73 <i>Y</i>[<i>k</i><sub>0</sub>, <i>k</i><sub>1</sub>, ...,
cannam@95 74 <i>k</i><sub><i>d-1</i></sub>] = <i>Y</i>[<i>n</i><sub>0</sub> -
cannam@95 75 <i>k</i><sub>0</sub>, <i>n</i><sub>1</sub> - <i>k</i><sub>1</sub>, ...,
cannam@95 76 <i>n</i><sub><i>d-1</i></sub> - <i>k</i><sub><i>d-1</i></sub>]<sup>*</sup>(where each dimension is periodic). Because of this symmetry, we only
cannam@95 77 store the
cannam@95 78 <i>k</i><sub><i>d-1</i></sub> = 0...<i>n</i><sub><i>d-1</i></sub>/2+1elements of the <em>last</em> dimension (division by 2 is rounded
cannam@95 79 down). (We could instead have cut any other dimension in half, but the
cannam@95 80 last dimension proved computationally convenient.) This results in the
cannam@95 81 peculiar array format described in more detail by <a href="Real_002ddata-DFT-Array-Format.html#Real_002ddata-DFT-Array-Format">Real-data DFT Array Format</a>.
cannam@95 82
cannam@95 83 <p>The multi-dimensional c2r transform is simply the unnormalized inverse
cannam@95 84 of the r2c transform. i.e. it is the same as FFTW's complex backward
cannam@95 85 multi-dimensional DFT, operating on a Hermitian input array in the
cannam@95 86 peculiar format mentioned above and outputting a real array (since the
cannam@95 87 DFT output is purely real).
cannam@95 88
cannam@95 89 <p>We should remind the user that the separable product of 1d transforms
cannam@95 90 along each dimension, as computed by FFTW, is not always the same thing
cannam@95 91 as the usual multi-dimensional transform. A multi-dimensional
cannam@95 92 <code>R2HC</code> (or <code>HC2R</code>) transform is not identical to the
cannam@95 93 multi-dimensional DFT, requiring some post-processing to combine the
cannam@95 94 requisite real and imaginary parts, as was described in <a href="The-Halfcomplex_002dformat-DFT.html#The-Halfcomplex_002dformat-DFT">The Halfcomplex-format DFT</a>. Likewise, FFTW's multidimensional
cannam@95 95 <code>FFTW_DHT</code> r2r transform is not the same thing as the logical
cannam@95 96 multi-dimensional discrete Hartley transform defined in the literature,
cannam@95 97 as discussed in <a href="The-Discrete-Hartley-Transform.html#The-Discrete-Hartley-Transform">The Discrete Hartley Transform</a>.
cannam@95 98
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