What is the relationship between Fourier transforms and Plancherel's theorem?

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In summary, the conversation was about a question on Fourier transform, specifically part (a) and (b) of the question. The equations and theorems used were provided, and part (a) was successfully solved. However, there was confusion on how to apply Plancherel's theorem in part (b) due to the difference in the function inside the modulus. It was mentioned that both f and its Fourier transform have a "moderate decrease" and it was assumed that part (a) would be used to answer part (b). Help was requested in understanding how to calculate with this difference in mind.
  • #1
titaniumx3
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Fourier transform question

Homework Statement



http://img410.imageshack.us/img410/852/question3jh8.gif

Homework Equations



I will be using the following definitions and theorems:

http://img338.imageshack.us/img338/4173/moderatedecreasevd4.gif

http://img260.imageshack.us/img260/7461/fouriertransonmodzo5.gif

http://img338.imageshack.us/img338/3530/plancherelmodvv2.gif


The Attempt at a Solution



I've done part (a) and shown that the Fourier transform of [tex]f(x)[/tex] is [tex]4\,{\frac { \left( \sin \left( \pi \,\xi \right) \right) ^{2}}{{\xi}^
{2}}}[/tex] but on part (b) I am a bit lost. I know how to apply Plancherel's theorem but the function inside the modulus (i.e. [tex]{\frac { \left( \sin \left( \xi \right) \right) ^{2}}{{\xi}^{2}}}[/tex]) is slightly different to the Fourier transform I got previously and I'm not sure how to relate them.

Please help!
 
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  • #2
BTW, I've shown f and it's Fourier transform are both functions of "moderate decrease". I'm also assuming you have to use part (a) to answer part (b). If not, how would you calculate something like that?
 
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  • #3
:grumpy:
 

What is the Fourier transform?

The Fourier transform is a mathematical operation that decomposes a function or signal into its constituent frequencies. It is commonly used in signal processing, image processing, and other areas of science and engineering.

Why is the Fourier transform important?

The Fourier transform is important because it allows us to analyze complex signals and systems in terms of simpler sinusoidal components. This makes it a useful tool for understanding and manipulating signals and data in various applications.

How is the Fourier transform calculated?

The Fourier transform is calculated by taking the integral of a function over all possible frequencies. In practice, this can be done using mathematical formulas or by using computer algorithms.

What is the difference between the Fourier transform and the inverse Fourier transform?

The Fourier transform converts a function from its time or space domain to its frequency domain, while the inverse Fourier transform converts it back from frequency domain to time or space domain.

What are some applications of the Fourier transform?

The Fourier transform has many applications in science and engineering, including signal and image processing, audio and video compression, data compression, and solving differential equations. It is also used in fields such as astronomy, chemistry, and medical imaging.

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