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			130 lines
		
	
	
		
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								<!-- This manual is for FFTW
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								(version 3.3.10, 10 December 2020).
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								Copyright (C) 2003 Matteo Frigo.
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								Copyright (C) 2003 Massachusetts Institute of Technology.
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								<title>The Discrete Hartley Transform (FFTW 3.3.10)</title>
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								<link href="Concept-Index.html" rel="index" title="Concept Index">
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								<link href="index.html#SEC_Contents" rel="contents" title="Table of Contents">
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								<link href="More-DFTs-of-Real-Data.html" rel="up" title="More DFTs of Real Data">
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								<link href="Other-Important-Topics.html" rel="next" title="Other Important Topics">
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								<link href="Real-even_002fodd-DFTs-_0028cosine_002fsine-transforms_0029.html" rel="prev" title="Real even/odd DFTs (cosine/sine transforms)">
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								<span id="The-Discrete-Hartley-Transform"></span><div class="header">
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								<p>
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								Previous: <a href="Real-even_002fodd-DFTs-_0028cosine_002fsine-transforms_0029.html" accesskey="p" rel="prev">Real even/odd DFTs (cosine/sine transforms)</a>, Up: <a href="More-DFTs-of-Real-Data.html" accesskey="u" rel="up">More DFTs of Real Data</a>   [<a href="index.html#SEC_Contents" title="Table of contents" rel="contents">Contents</a>][<a href="Concept-Index.html" title="Index" rel="index">Index</a>]</p>
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								<hr>
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								<span id="The-Discrete-Hartley-Transform-1"></span><h4 class="subsection">2.5.3 The Discrete Hartley Transform</h4>
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								<p>If you are planning to use the DHT because you’ve heard that it is
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								“faster” than the DFT (FFT), <strong>stop here</strong>.  The DHT is not
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								faster than the DFT.  That story is an old but enduring misconception
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								that was debunked in 1987.
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								</p>
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								<p>The discrete Hartley transform (DHT) is an invertible linear transform
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								closely related to the DFT.  In the DFT, one multiplies each input by
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								<em>cos - i * sin</em> (a complex exponential), whereas in the DHT each
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								input is multiplied by simply <em>cos + sin</em>.  Thus, the DHT
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								transforms <code>n</code> real numbers to <code>n</code> real numbers, and has the
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								convenient property of being its own inverse.  In FFTW, a DHT (of any
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								positive <code>n</code>) can be specified by an r2r kind of <code>FFTW_DHT</code>.
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								<span id="index-FFTW_005fDHT"></span>
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								<span id="index-discrete-Hartley-transform"></span>
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								<span id="index-DHT"></span>
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								</p>
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								<p>Like the DFT, in FFTW the DHT is unnormalized, so computing a DHT of
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								size <code>n</code> followed by another DHT of the same size will result in
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								the original array multiplied by <code>n</code>.
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								<span id="index-normalization-4"></span>
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								</p>
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								<p>The DHT was originally proposed as a more efficient alternative to the
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								DFT for real data, but it was subsequently shown that a specialized DFT
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								(such as FFTW’s r2hc or r2c transforms) could be just as fast.  In FFTW,
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								the DHT is actually computed by post-processing an r2hc transform, so
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								there is ordinarily no reason to prefer it from a performance
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								perspective.<a id="DOCF5" href="#FOOT5"><sup>5</sup></a>
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								However, we have heard rumors that the DHT might be the most appropriate
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								transform in its own right for certain applications, and we would be
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								very interested to hear from anyone who finds it useful.
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								</p>
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								<p>If <code>FFTW_DHT</code> is specified for multiple dimensions of a
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								multi-dimensional transform, FFTW computes the separable product of 1d
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								DHTs along each dimension.  Unfortunately, this is not quite the same
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								thing as a true multi-dimensional DHT; you can compute the latter, if
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								necessary, with at most <code>rank-1</code> post-processing passes
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								[see e.g. H. Hao and R. N. Bracewell, <i>Proc. IEEE</i> <b>75</b>, 264–266 (1987)].
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								</p>
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								<p>For the precise mathematical definition of the DHT as used by FFTW, see
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								<a href="What-FFTW-Really-Computes.html">What FFTW Really Computes</a>.
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								</p>
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								<div class="footnote">
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								<hr>
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								<h4 class="footnotes-heading">Footnotes</h4>
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								<h5><a id="FOOT5" href="#DOCF5">(5)</a></h3>
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								<p>We provide the DHT mainly as a byproduct of some
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								internal algorithms. FFTW computes a real input/output DFT of
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								<em>prime</em> size by re-expressing it as a DHT plus post/pre-processing
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								and then using Rader’s prime-DFT algorithm adapted to the DHT.</p>
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								</div>
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								<hr>
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								<div class="header">
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								<p>
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								Previous: <a href="Real-even_002fodd-DFTs-_0028cosine_002fsine-transforms_0029.html" accesskey="p" rel="prev">Real even/odd DFTs (cosine/sine transforms)</a>, Up: <a href="More-DFTs-of-Real-Data.html" accesskey="u" rel="up">More DFTs of Real Data</a>   [<a href="index.html#SEC_Contents" title="Table of contents" rel="contents">Contents</a>][<a href="Concept-Index.html" title="Index" rel="index">Index</a>]</p>
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