**NOTE: THIS DOCUMENT IS OBSOLETE, PLEASE CHECK THE NEW
VERSION:** "Mathematics of the Discrete
Fourier Transform (DFT), with Audio Applications --- Second
Edition", by Julius
O. Smith III, W3K
Publishing, 2007, ISBN 978-0-9745607-4-8. - Copyright ©
*2017-09-28* by Julius O. Smith III -
Center for Computer Research
in Music and Acoustics (CCRMA), Stanford University

**
<< Previous page TOC INDEX Next
page >>**

Appendix D: The Similarity TheoremThe

similarity theoremis fundamentally restricted to thecontinuous-time case. It says that if you ''stretch'' a signal by the factor in the time domain, you ''squeeze'' its Fourier transform by the same factor in the frequencydomain. This is such a fundamental Fourier relationship, that we include it here rather than leave it out as a non-DFT result.The closest we came to the similarity theorem among the DFT theorems was the the Interpolation Theorem. We found that ''stretching'' a

discrete-timesignal by the integer factor (filling in between samples with zeros) corresponded to the spectrum beingrepeatedtimes around the unit circle. As a result, the ''baseband'' copy of the spectrum ''shrinks'' in width (relative to ) by the factor . Similarly, stretching a signal usinginterpolation(instead of zero-fill) corresponded to the repeated spectrum with all spurious spectral copies zeroed out. The spectrum of the interpolated signal can therefore be seen as having been stretched by the inverse of the time-domain stretch factor. In summary, the Interpolation DFT Theorem can be viewed as the discrete-time counterpart of the similarity Fourier Transform (FT) theorem.

Theorem:For all continuous-time functions possessing a Fourier transform,

where

and is any nonzero real number (the abscissa scaling factor).

Proof:

The absolute value appears above because, when , , which brings out a minus sign in front of the integral fromto.