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| <center> <math> \frac{1}{2 \pi}(F \star G )(\omega) = \int_{-\infty}^{\infty}f(t) g(t) e^{i \omega t } \; dt. </math> </center> | | <center> <math> \frac{1}{2 \pi}(F \star G )(\omega) = \int_{-\infty}^{\infty}f(t) g(t) e^{i \omega t } \; dt. </math> </center> |
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| + | (The extra factor of <math> 1/2 \pi </math> echoes what is seen in other results involving the Fourier transform, such as [[Parseval's relation]]. |
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| To come full circle, if we were to perform the inverse Fourier transform of <math> F(\omega) </math> we would need to treat this as a contour integral, and choose | | To come full circle, if we were to perform the inverse Fourier transform of <math> F(\omega) </math> we would need to treat this as a contour integral, and choose |
| the contour along the real axis to pass over any poles that would be on the real axis, to obtain the causal function <math> f(t). </math> | | the contour along the real axis to pass over any poles that would be on the real axis, to obtain the causal function <math> f(t). </math> |
Revision as of 14:09, 7 December 2016
The Fourier transform of the convolution of two functions is equal to the product of their individual transforms (or multiplying their amplitude spectra and summing their phase spectra). See Figures F-20 and F-22.
Integral definition
The process of convolution of two functions
and
is defined in one dimension, as
Fourier domain equivalent
We may replace
and
by their Fourier domain representations
and
where
and
are the Fourier transforms of
and
respectively.
Substituting these representations into the original integral representation of convolution yields
We may rearrange the order of integrations
Recognizing the factor in
as the frequency domain representation of the Dirac delta function,
permits us to write the equivalent expression
The
integral may be performed, exploiting the sifting property of the delta function to convert the
to
yields the equivalence of
multiplication in the frequency domain to convolution in the time domain
Convolution in the Frequency domain
Similarly, multiplication in the time domain may be interpreted as convolution in the frequency domain, to within a constant factor. Such
a frequency domain convolution representation is useful, for example, if we were interested in finding the Fourier transform of the product of functions
of known Fourier transform.
Paralleling the derivation above, we write the convolution in the frequency domain
As above, we substitute the Fourier representations of
and
and
As in the derivation above, we substitute the Fourier representations of
and
and rearrange the terms to yield
We recognize the term in
as the Fourier form of the Dirac delta function
As before, we apply the sifting property of the delta function, in this case to perform the
integration to yield
There is an extra factor of
Thus, if we were representing the Fourier transform of the product
as the Frequency domain convolution of their respective Fourier transforms, we
would need to include a factor of
in the convolution
(The extra factor of
echoes what is seen in other results involving the Fourier transform, such as Parseval's relation.
To come full circle, if we were to perform the inverse Fourier transform of
we would need to treat this as a contour integral, and choose
the contour along the real axis to pass over any poles that would be on the real axis, to obtain the causal function