What Causes Repetition in Fourier Transforms of Audio and Visual Data?

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Discussion Overview

The discussion revolves around the properties of Fourier transforms, particularly focusing on the conditions under which repeated Fourier transforms yield the same or related results. Participants explore the implications of these properties for various functions, including the Gaussian function, and the mathematical relationships between forward and inverse transforms.

Discussion Character

  • Exploratory
  • Technical explanation
  • Debate/contested
  • Mathematical reasoning

Main Points Raised

  • One participant questions when repeated Fourier transforms (twice or more) yield the same result as the first transform, seeking specific functions that exhibit this property.
  • Another participant notes that the Fourier transform and its inverse have similar kernels, which may relate to the concerns raised about repetition.
  • A participant explains that applying the Fourier transform twice results in a function that is the mirror image of the original function, provided the original function is sufficiently smooth.
  • It is mentioned that the Fourier transform of a Gaussian function is also a Gaussian, suggesting that there may be other functions with similar properties, although specific examples are not provided.
  • One participant indicates that a quick search reveals multiple functions that are self-Fourier transforms, implying a broader range of examples exists.
  • Discussion includes technical details about the forward and inverse transforms, emphasizing the role of sign conventions in their definitions.
  • Some participants share informal comments and examples related to audio and visual data transformations, contributing to the exploratory nature of the discussion.

Areas of Agreement / Disagreement

Participants express various viewpoints regarding the properties of Fourier transforms, with some agreeing on the nature of the transformations and others raising questions or suggesting further exploration. No consensus is reached on specific functions that maintain their form under repeated transformations.

Contextual Notes

Participants reference the need for sufficient smoothness of functions for certain properties to hold, and there are mentions of conventions in the definitions of Fourier transforms that may affect interpretations.

Who May Find This Useful

This discussion may be of interest to those studying Fourier analysis, signal processing, or related mathematical fields, particularly individuals curious about the implications of repeated transformations in various contexts.

mertcan
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I would like to express that when I am viewing the repetitive Fourier transform on Internet I encounter that for instance twice Fourier transform may lead the same value at the end of first Fourier transform. When does repetitive( twice or third... consecutively)fourier transform be same with the first Fourier transform? Or what kind of functions have this property when they are transformed according to fourier??
 
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Fourier transform and inverse transform have almost identical kernels e^{itx} \ and\ e^{-itx}. That might explain your concern.
 
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mertcan said:
I would like to express that when I am viewing the repetitive Fourier transform on Internet I encounter that for instance twice Fourier transform may lead the same value at the end of first Fourier transform. When does repetitive( twice or third... consecutively)fourier transform be same with the first Fourier transform? Or what kind of functions have this property when they are transformed according to fourier??

@mathman is right. In detail:

If for any function ##f## from reals to complex numbers, we define ##F(f)## to be that function ##\tilde{f}## such that:

##\tilde{f}(y) = \frac{1}{\sqrt{2\pi}}\int f(x) e^{-iyx} dx##

Then ##F(F(f))## is that function ##f'## such that ##f'(x) = f(-x)##.

So a double transform returns you almost to where you started, except the mirror-image. ##F(F(F(F(f))))## will always be equal to ##f##. (Well, if ##f## is sufficiently smooth, anyway.)
 
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The Fourier transform of a Gaussian gives a Gaussian. There may be other functions that have this property but I have never seen one. Are you looking for a proof of a functional form that is preserved under repeated Fourier transformation operations? Maybe a mathematician on this forum can point you to literature on the subject.

Peace
Fred
 
A quick google search for self Fourier transforms gives a host of references...

There are multiple functions that have this property.
 
Just it's inverse... sort of at least, the only difference between a forward transform and an inverse transform is the sign of the exponential and the initial data... So apply Euler's formula and have X[k] = x[n]*(cos(-2.0*k*n*pi/frame_size) + i*sin(-2.0*k*n*pi/frame_size)) or for the inverse, x[n] = X[k]*(cos(2.0*k*n*pi/frame_size) + i*sin(2.0*k*n*pi/frame_size)). Video sample here:



The example is slight more complicated because a z transform is used...

I'm taking things slow, because I would like to understand the butterfly idea with going fast; anyone got any hints for me?

EDIT:
I'm sort of casual with my explaining. I presume that you already understand this material like me.

A forward Fourier transform will bring you to the transform domain. The transform domain's data is the magnitude and phase of the signal. The magnitude is displayed in red above.

An inverse Fourier transform takes the transform data and brings it back to the time domain; shown above as the yellow signal.
 
Last edited:
just for fun:

 
yet another:

 
mathman said:
Fourier transform and inverse transform have almost identical kernels
eitx and e−itxeitx and e−itx​
e^{itx} \ and\ e^{-itx}. That might explain your concern.

A forward transform has a negative sign, the inverse is positive...
 
  • #10
ADDA said:
A forward transform has a negative sign, the inverse is positive...
Yes, but that is a matter of convention, just like there are two conventions for the factor of (2\pi)^{-n} in front of the integral.
 
  • #11
Dr Transport said:
Yes, but that is a matter of convention, just like there are two conventions for the factor of (2\pi)^{-n} in front of the integral.

It might be a convention as to whether you use a + sign or - sign in the definition of the Fourier transform, but it's absolutely necessary that the inverse uses the opposite sign.
 
  • #13
just for fun:

60HZ frame rate audio or a 44.1k sample rate

3HZ visual frames

The green signal would be a representation of the left channel or the data received by your stereo or phone. The background data transforms that green signal to the top yellow signal or original audio in blue.

 

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