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Scaling Theorem

The scaling theorem (or similarity theorem) provides that if you horizontally ``stretch'' a signal by the factor $ \alpha $ in the time domain, you ``squeeze'' and amplify its Fourier transform by the same factor in the frequency domain. This is an important general Fourier duality relationship.



Theorem: For all continuous-time functions $ x(t)$ possessing a Fourier transform,

$\displaystyle \zbox {\hbox{\sc Stretch}_\alpha(x) \;\longleftrightarrow\;\left\vert\alpha\right\vert\hbox{\sc Stretch}_{(1/\alpha)}(X)}
$

where

$\displaystyle \hbox{\sc Stretch}_{\alpha,t}(x) \isdef x\left(\frac{t}{\alpha}\right)
$

and $ \alpha $ is any nonzero real number (the abscissa stretch factor). A more commonly used notation is the following:

$\displaystyle \zbox {x\left(\frac{t}{\alpha}\right) \;\longleftrightarrow\;
\left\vert\alpha\right\vert\cdot X(\alpha\omega)}
$



Proof: Taking the Fourier transform of the stretched signal gives

\begin{eqnarray*}
\hbox{\sc FT}_{\omega}(\hbox{\sc Stretch}_\alpha(x))
&\isdef ...
...\tau \\
&\isdef & \left\vert\alpha\right\vert X(\alpha\omega).
\end{eqnarray*}

The absolute value appears above because, when $ \alpha<0$, $ d
(\alpha\tau) < 0$, which brings out a minus sign in front of the integral from $ -\infty$ to $ \infty$.

The scaling theorem is fundamentally restricted to the continuous-time, continuous-frequency (Fourier transform) case. The closest we will come to the scaling theorem among the DTFT theorems (§2.3) is the stretch (repeat) theorem (page [*]).


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``Spectral Audio Signal Processing'', by Julius O. Smith III, (March 2007 Draft).
Copyright © 2008-05-20 by Julius O. Smith III
Center for Computer Research in Music and Acoustics (CCRMA),   Stanford University
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