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Power Theorem

The power theorem for Fourier transforms states that the inner product of two signals in the time domain equals their inner product in the frequency domain.

The inner product of two spectra $ X(\omega)$ and $ Y(\omega)$ may be defined as

$\displaystyle \left<X,Y\right> \isdef
\frac{1}{2\pi}
\ensuremath{\int_{-\infty...
...d\omega
= \ensuremath{\int_{-\infty}^{\infty}}X(2\pi f)\overline{Y(2\pi f)}df.
$

This expression can be interpreted as the inverse Fourier transform of $ X\cdot\overline{Y}$ evaluated at $ t=0$:

$\displaystyle \left<X,Y\right> \isdef
\frac{1}{2\pi}
\left.\ensuremath{\int_{-...
...^{\infty}}X(\omega)\overline{Y(\omega)}e^{j\omega t}d\omega\right\vert _{t=0}.
$

By the convolution theorem2.4.6) and flip theorem2.4.7),

$\displaystyle X\cdot \overline{Y}\;\longleftrightarrow\; x\ast \hbox{\sc Flip}(\overline{y}),
$

which at $ t=0$ gives

$\displaystyle (x\ast \hbox{\sc Flip}(\overline{y}))(0) = \left.\ensuremath{\int...
...\int_{-\infty}^{\infty}}x(\tau)\overline{y(\tau)}d\tau \isdef \left<x,y\right>
$

Thus,

$\displaystyle \zbox {\left<x,y\right> \longleftrightarrow \left<X,Y\right>.}
$


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[How to cite this work]  [Order a printed hardcopy]

``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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