Fourier transform of the auto correlation function to get energy

In summary: You can think of them as nested, so that you're doing the T integral for each fixed value of t. In summary, the Fourier transform of the auto correlation function is the energy spectral density (ESD) of a signal. In the given conversation, the order of integration was changed, resulting in the second expression being obtained. This was done by pulling the exponential into the inside integral and then switching the order of integration.
  • #1
thomas49th
655
0

Homework Statement



The Fourier transform of the auto correlation function is the energy spectral density (ESD) of a signal. Here is the "apparent" proof:

[tex]\int e^{-jwT} [ \int g(t)g(t+T)dt] dT[/tex]
=> [tex]\int g(t)[ \int g(T+t)e^{-jwT}dT] dt[/tex]

What happened here? Why did the second integral change from t to T, why did t+T turn to T+t and the exponent change from jwt to jwT?

Thanks
Thomas
 
Last edited:
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  • #2
Your first expression looks wrong.
thomas49th said:

[tex]\int e^{-jwt} [ \int g(t)g(t+T)dt] dt[/tex]


IF the first integral (the one inside []) is over t, then the resulting function is independent of t, so second integral with the same t will be trivial. You might want to check the source again for a possible typo. Here is what I think it should look like

[tex]\int e^{-jwT} [ \int g(t)g(t+T)dt] dT[/tex]

From which the second expression can be obtained.
 
  • #3
you're right - i amended it in the first post. but I'm still stuck on it :\
 
Last edited:
  • #4
They're just changing the order of integration.
 
  • #5
sorry... i don't see? How can you just flip around variables of function arguments?
 
  • #6
You can pull the exponential into the inside integral to get

[tex]\int e^{-jwT} \int g(t) g(t+T)\,dt\,dT = \int \int e^{-jwT} g(t) g(t+T)\,dt\,dT[/tex]

Now switch the order of integration and then pull out the factors that don't depend on T from the inside integral.
 
  • #7
what do you mean by order of integration. A quick Google seems to point me at double integration. Something which I haven't done yet. If it is double integration I question the material of my course, seeing as they haven't introduced that concept yet.
 
  • #8
Well, you have two integral signs, right? That's a double integration, one with respect to t and one with respect to T.
 

1. What is a Fourier transform?

A Fourier transform is a mathematical technique that allows us to decompose a function into its individual frequency components. It is widely used in signal processing, image processing, and other fields of science and engineering.

2. What is the auto correlation function?

The auto correlation function is a measure of the similarity between a signal and a time-shifted version of itself. It is commonly used in signal processing to identify repeating patterns or periodic signals.

3. How does the Fourier transform of the auto correlation function calculate energy?

The Fourier transform of the auto correlation function calculates energy by decomposing the signal into its frequency components and summing the squared magnitudes of each component. This represents the energy contained within the signal at each frequency.

4. Why is the Fourier transform of the auto correlation function useful?

The Fourier transform of the auto correlation function is useful because it allows us to analyze the frequency content of a signal and determine the energy distribution within it. This can be helpful in understanding the characteristics and properties of a signal.

5. Are there any limitations or drawbacks to using the Fourier transform of the auto correlation function?

One limitation of using the Fourier transform of the auto correlation function is that it assumes the signal is periodic and stationary. This may not always be the case in real-world signals, leading to inaccuracies in the energy calculation. Additionally, the Fourier transform may not be able to accurately capture high-frequency components in a signal with a limited time domain.

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