Fourier Transform question, is it correct to remove the correcting factor?

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Discussion Overview

The discussion revolves around the normalization factor in the Fourier transform and its inverse, questioning whether it is necessary or optional. Participants explore different conventions and the implications of omitting the factor, with references to specific mathematical expressions and their correctness.

Discussion Character

  • Debate/contested, Technical explanation, Conceptual clarification

Main Points Raised

  • Some participants argue that the normalization factor is essential for obtaining the original function back after applying the Fourier transform and its inverse, while others suggest that it may not be necessary depending on the conventions used.
  • One participant points out that without the normalization factor, the result of the inverse transform would yield a scaled version of the original function (specifically, 2π times the original function).
  • There is a discussion about the definitions of the Fourier transform and inverse transform, with some participants questioning the correctness of the definitions provided in the original post.
  • Participants express confusion over the integration variables used in the Fourier transform equations, highlighting potential errors in the notes of the original poster.
  • One participant suggests that the original poster should clarify the conventions used by their professor to resolve discrepancies.

Areas of Agreement / Disagreement

Participants do not reach a consensus on the necessity of the normalization factor, with multiple competing views presented regarding its importance and the correctness of the definitions used.

Contextual Notes

There are unresolved issues regarding the integration variables in the Fourier transform equations, and participants note that the definitions may depend on specific conventions that are not clearly stated.

thecake
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My math professor doesn't include the correcting (normalizing factor) neither in the Fourier transform nor in the inverse Fourier! He says that it's optional.
It is weird because I have seen it used in all the textbooks! Is it a big deal?

He defines the Fourier transform as:-

http://img685.imageshack.us/img685/3822/56167015.jpg


And inverse as:-

http://img218.imageshack.us/img218/8430/25649157.jpg
 
Last edited by a moderator:
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You might want to take another look at the Fourier transforms in those pictures... They don't make sense.

As for your answer: yes, it does matter. The constant in front is a normalization factor. If you have a function f(x) and you Fourier transform it, followed by the inverse transform, then you should expect to get the same function back, f(x). But without the normalization factor you will always get back [itex]2\pi f(x)[/itex] -- which is why you need the normalization in front. Just try it out with some function like [itex]\sin(\pi x)[/itex]

You can also use the following conventions

[tex]F(\omega) = \int f(x) e^{-2\pi i \omega x} dx[/tex]
and for the inverse
[tex]f(x) = \int F(\omega) e^{2\pi i \omega x} dx[/tex]

No normalization is needed, but the [tex]2\pi[/tex] still pops up somewhere.
 
xepma said:
You might want to take another look at the Fourier transforms in those pictures... They don't make sense.

Well, that's what I have written in my notes, what's wrong?
Omega is the angular frequency
Inline28.gif

Though he never substitutes it.

xepma said:
As for your answer: yes, it does matter. The constant in front is a normalization factor. If you have a function f(x) and you Fourier transform it, followed by the inverse transform, then you should expect to get the same function back, f(x). But without the normalization factor you will always get back [itex]2\pi f(x)[/itex] -- which is why you need the normalization in front. Just try it out with some function like [itex]\sin(\pi x)[/itex]

So, should I go have a talk with him?


xepma said:
You can also use the following conventions

[tex]F(\omega) = \int f(x) e^{-2\pi i \omega x} dx[/tex]
and for the inverse
[tex]f(x) = \int F(\omega) e^{2\pi i \omega x} dx[/tex]

No normalization is needed, but the [tex]2\pi[/tex] still pops up somewhere.
But the questions are multiple choice, so if I use a different form I'd get a different answer :(
 
Last edited by a moderator:
thecake said:
Well, that's what I have written in my notes, what's wrong?
Omega is the angular frequency
Inline28.gif

Though he never substitutes it.
I'm afraid they can't be correct -- really. In the first you integrate over t, while the function f is a function of x. That means you can just pull this function out of the integral! The same goes for the inverse: you integrate over t, while the function F is a function of x... it simply doesn't make sense.

So:
[tex]\int f(x) e^{i\omega t} dt = f(x) \int e^{i\omega t} dt[/tex]

Do you see why this is true?




So, should I go have a talk with him?
If you're notes are incorrect, then you're teacher might still be right, depending on his conventions for the transform. It's best to ask him what conventions he uses precisely. I can assure you that what you've written here is either incorrect, or some information is missing.

But the questions are multiple choice, so if I use a different form I'd get a different answer :(

:/
 
Last edited by a moderator:
xepma said:
I'm afraid they can't be correct -- really. In the first you integrate over t, while the function f is a function of x. That means you can just pull this function out of the integral! The same goes for the inverse: you integrate over t, while the function F is a function of x... it simply doesn't make sense.

So:
[tex]\int f(x) e^{i\omega t} dt = f(x) \int e^{i\omega t} dt[/tex]

Do you see why this is true?





If you're notes are incorrect, then you're teacher might still be right, depending on his conventions for the transform. It's best to ask him what conventions he uses precisely. I can assure you that what you've written here is either incorrect, or some information is missing.



:/

You're right it is a function of (t) xD! Silly me. I've just checked.
So is he right after all?
 

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