Comparing Fourier Transforms of Rectangle and Triangular Functions

  • Thread starter UrbanXrisis
  • Start date
  • Tags
    Fourier
In summary, the conversation discusses the similarities between the Fourier transform of a rectangular function and a triangular function, and how they both result in sine functions due to the even symmetry and positivity of the functions. The relationship between the power of the function and the value of n in sin^n is also discussed, with the suggestion to calculate the Fourier transform of a function bx^2 to see that it results in sin^3. The concept of convolutions is also mentioned as a way to understand the transform of a function, with the question of how to produce x^2 with a convolution and what its transform would be.
  • #1
UrbanXrisis
1,196
1

Homework Statement



For a visual of what I am talking about, please visit: http://webhost.etc.tuiasi.ro/cin/Downloads/Fourier/Fourier.html
and scroll down to the "Examples of Fourier Transforms" part

I am ask to explain why the Fourier transform on the rectangle function was similar to the Fourier transform on the trangular function.

Homework Equations





The Attempt at a Solution



so here what I think, and I'm not totally sure about it. The FT of a rectangular function is sin and rhe FT of the trangular function is a sin^2. The FT are similar because both functions are even, symetric, and always positive. The rectangular function is a constant function, which gives the sin, while the trangular function is a linear function, which gives the sin^2. Maybe a x^2 function with bounds will give a sin^3? not really sure about that. Is my reasoning correct for why the two FTs are similar?
 
Physics news on Phys.org
  • #2
Can't you calculate the FT of x^2 function? it should be easy..
define a function bx^2 between -a and a , and see what the FT would be..
 
  • #3
ok i did it, and it does show that it would be sin^3

know this, why is it that the higher the power, the larger n is for sin^n?
 
  • #4
First notice that the transform of a square pulse is sin(aw)/(aw) which is called sinc(aw). It is not the same as a simple sine.

To answer your question, here's a different approach--think in terms of convolutions. The convolution of a square pulse with itself is what? (It should be in your book.) Therefore what is the transform of the convolution?

As for x^2, how would you produce that with a convolution and what is its transform?
 

FAQ: Comparing Fourier Transforms of Rectangle and Triangular Functions

What is a Fourier transform?

A Fourier transform is a mathematical tool used to break down a complex signal into its individual frequency components. It allows us to analyze and understand the frequency content of a signal, helping us to identify patterns and relationships within the data.

How is a Fourier transform calculated?

A Fourier transform is calculated by taking a signal, typically represented as a function of time, and converting it into a function of frequency. This is done by decomposing the signal into a sum of sinusoidal waves with different frequencies and amplitudes, using complex numbers and integrals.

What is the difference between a Fourier transform and a Fourier series?

A Fourier transform is used for continuous signals, while a Fourier series is used for periodic signals. A Fourier transform converts a signal into a function of frequency, while a Fourier series decomposes a periodic signal into a sum of sinusoidal waves with different frequencies and amplitudes.

What are the practical applications of Fourier transforms?

Fourier transforms have a wide range of applications in various fields, including signal processing, image processing, data compression, and differential equations. They are also used in many scientific and engineering disciplines, such as physics, chemistry, and biology, for analyzing and visualizing data.

Are there any limitations to using Fourier transforms?

While Fourier transforms are a powerful tool, they do have some limitations. They assume that the signal is stationary, meaning it does not change over time. They also require the signal to be continuous and infinitely differentiable, which may not always be the case in real-world scenarios. Additionally, the interpretation of the results can be complex and may require advanced mathematical knowledge.

Similar threads

Replies
1
Views
1K
Replies
2
Views
2K
Replies
3
Views
2K
Replies
2
Views
3K
Replies
5
Views
1K
Replies
1
Views
1K
Back
Top