Inverse Fourier Transformation of a Fourier Transformation

In summary, the conversation is discussing the inverse transformation of a Fourier transformed function, which involves integrating over a range of variables and manipulating the equations to arrive at the correct solution. The final result is a Dirac delta function, and the conversation also addresses the issue of normalization.
  • #1
SwordSmith
8
0
I am having problem with the inverse transformation of a Fourier transformed function which should give the function itself.

Let

[itex]f=f(x)[/itex] and let f be Fourier transformable (whatever that implies)

Let

[itex]\tilde{f}(k)=∫^{\infty}_{-\infty}dx e^{-ikx}f(x)[/itex] (1)

then we should have:

[itex]f(x)=∫^{\infty}_{-\infty}dk e^{ikx}f(k)[/itex] (2)

This implies:

[itex]f(x)=∫^{\infty}_{-\infty}dk e^{ikx}∫^{\infty}_{-\infty}dx' e^{-ikx'}f(x')[/itex] (3)

Note that x'≠x

My solution is as follows:
[itex]f(x)=∫^{\infty}_{-\infty}dk e^{ikx}∫^{\infty}_{-\infty}dx' e^{-ikx'}f(x')[/itex] (4)

[itex]f(x)=∫^{\infty}_{-\infty}dk ∫^{\infty}_{-\infty}dx' e^{-ik(x'-x)}f(x')[/itex] (5)

[itex]f(x)=∫^{\infty}_{-\infty}dx' ∫^{\infty}_{-\infty}dk e^{-ik(x'-x)}f(x')[/itex] (6)

[itex]f(x)=∫^{\infty}_{-\infty}dx' δ(x'-x)f(x')[/itex] (7)

[itex]f(x)=f(x)[/itex] (8)

Is this correct? Step (6) to (7) bothers me. And what about the change in integration variables? I guess that is correct as well?
 
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  • #2
This looks correct to me. In step 6 you can move f(x') from the right integral into the left one, leaving int{ dk exp(-ik(x'-x)) }. This becomes the delta function in 7 as you state, through application of the principle of stationary phase.
 
  • #3
The analysis is essentially correct, except that you need to include 2π in the exponents. That is 2πikx or -2πikx'.
 
  • #4
Oh, right! Mathman points out that I left off the normalization--sorry! You can solve the problem using the variables he mentions, or you can continue to use k but then the inverse transform has a normalizing constant 1/2π in front like this:

[tex]f(x)=\frac{1}{2\pi}∫^{\infty}_{-\infty} e^{ikx}\tilde{f}(k)dk.[/tex]
The key piece of eq. (6) becomes

[tex]\frac{1}{2\pi}∫^{\infty}_{-\infty} e^{ik(x'-x)}dk[/tex]
which is evaluated most easily as a limit

[tex]\frac{1}{2\pi}\lim_{r\rightarrow\infty}∫^{r}_{-r} e^{ik(x'-x)}dk.[/tex]
The integral becomes

[tex]\lim_{r\rightarrow\infty}r\frac{\sin r(x'-x)}{r(x'-x)}[/tex]
which is single-valued only if x'=x. At that point the ratio equals one by L'Hospital's rule, the overall expression becomes infinite, and this expression is a Dirac delta function.
 

Related to Inverse Fourier Transformation of a Fourier Transformation

1. What is the purpose of performing an Inverse Fourier Transformation?

The Inverse Fourier Transformation is used to convert a Fourier transformation back to its original form. This is useful in many fields of science and engineering, as it allows for the analysis of signals and data in the time domain.

2. How is the Inverse Fourier Transformation calculated?

The Inverse Fourier Transformation is calculated using a mathematical formula that involves taking the complex conjugate of the Fourier transform and dividing it by the length of the original signal. This process is typically done using software or programming languages such as MATLAB or Python.

3. What is the difference between a Fourier Transformation and an Inverse Fourier Transformation?

A Fourier Transformation converts a signal from the time domain to the frequency domain, while an Inverse Fourier Transformation converts it back to the time domain. Essentially, one is the inverse of the other.

4. Why is the Inverse Fourier Transformation important in signal processing?

The Inverse Fourier Transformation is important in signal processing because it allows for the analysis and manipulation of signals in the time domain. This is useful in applications such as audio and image processing, where signals need to be analyzed and modified in their original form.

5. Can an Inverse Fourier Transformation be applied to any signal?

Yes, an Inverse Fourier Transformation can be applied to any signal that has a Fourier Transformation. This includes continuous signals, discrete signals, and even signals that are not periodic. However, the signal must have a finite energy for the transformation to be valid.

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