Generate the Fourier transform of the function

In summary: It looks OK so far. You have an expression for the Fourier transform of ##f_d##:$$\hat{f_d}(p) = \sqrt{\frac{2}{\pi}} e^{-ipd} \frac{\sin(pa)}{pa}$$You need an expression for the Fourier transform of ##f_{kd}## where ##k## is an arbitrary integer. This will obviously be$$\hat{f_{kd}}(p) = \sqrt{\frac{2}{\pi}} e^{-ipkd} \frac{\sin(pa)}{pa}$$Now apply linearity. You want the Fourier
  • #1
Poirot
94
2

Homework Statement


a(x)=f-Nd(x) + f-(N-1)d(x) +...+ f(N-1)d(x) + fNd

Homework Equations


fd(x) = (1/a for |x-d| < a and 0 otherwise)
Fourier transform of function g(x) is g~(p) = 1/root(2pi) ∫ dx e-ipx g(x)

The Attempt at a Solution


[/B]
I have found the general Fourier transform for the function fd(x) and got:
f~(p) = root(2/pi) e-ipd sin(pa)/pa

I then tried to use the linearity of Fourier transform and added the solutions for f(x) but subbed in the various N, N-1 etc but got muddled up and a little confused.

Is this the right thing to be doing? Is this going to come out as a nice clean answer?

Thanks in advance.
 
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  • #2
It looks OK so far. You have an expression for the Fourier transform of ##f_d##:
$$\hat{f_d}(p) = \sqrt{\frac{2}{\pi}} e^{-ipd} \frac{\sin(pa)}{pa}$$
You need an expression for the Fourier transform of ##f_{kd}## where ##k## is an arbitrary integer. This will obviously be
$$\hat{f_{kd}}(p) = \sqrt{\frac{2}{\pi}} e^{-ipkd} \frac{\sin(pa)}{pa}$$
Now apply linearity. You want the Fourier transform of
$$\sum_{k=-N}^{N}f_{kd}(x)$$
which is
$$\sum_{k=-N}^{N}\hat{f_{kd}}(p) = \sum_{k=-N}^{N} \sqrt{\frac{2}{\pi}} e^{-ipkd} \frac{\sin(pa)}{pa}$$
Can you see how to simplify this?
 
  • #3
jbunniii said:
It looks OK so far. You have an expression for the Fourier transform of ##f_d##:
$$\hat{f_d}(p) = \sqrt{\frac{2}{\pi}} e^{-ipd} \frac{\sin(pa)}{pa}$$
You need an expression for the Fourier transform of ##f_{kd}## where ##k## is an arbitrary integer. This will obviously be
$$\hat{f_{kd}}(p) = \sqrt{\frac{2}{\pi}} e^{-ipkd} \frac{\sin(pa)}{pa}$$
Now apply linearity. You want the Fourier transform of
$$\sum_{k=-N}^{N}f_{kd}(x)$$
which is
$$\sum_{k=-N}^{N}\hat{f_{kd}}(p) = \sum_{k=-N}^{N} \sqrt{\frac{2}{\pi}} e^{-ipkd} \frac{\sin(pa)}{pa}$$
Can you see how to simplify this?
I don't think it's the way I'm supposed to do it as my lecturer gave a formula as a hint:
1/(x2 + 1/x(N-1) + 1 ... + xN + x(N-1) = (x-(N+1/2) - x(N+1/2)) / (x-1/2 - x1/2)
But I can't see how to manipulate the summation into this as there's the extra part in the exponent?
However I had an idea; as the terms go from -N to N, there will always be a term with the negative of that exponent added to it, so can I use e-ix + eix = 2cos(x) and then add 1 due to the term when k=0?
 
  • #4
Poirot said:
I don't think it's the way I'm supposed to do it as my lecturer gave a formula as a hint:
1/(x2 + 1/x(N-1) + 1 ... + xN + x(N-1) = (x-(N+1/2) - x(N+1/2)) / (x-1/2 - x1/2)
But I can't see how to manipulate the summation into this as there's the extra part in the exponent?
However I had an idea; as the terms go from -N to N, there will always be a term with the negative of that exponent added to it, so can I use e-ix + eix = 2cos(x) and then add 1 due to the term when k=0?
Realised this wouldn't solve the issue of the summation, just a slightly prettier equations :(
 
  • #5
jbunniii said:
It looks OK so far. You have an expression for the Fourier transform of ##f_d##:
$$\hat{f_d}(p) = \sqrt{\frac{2}{\pi}} e^{-ipd} \frac{\sin(pa)}{pa}$$
You need an expression for the Fourier transform of ##f_{kd}## where ##k## is an arbitrary integer. This will obviously be
$$\hat{f_{kd}}(p) = \sqrt{\frac{2}{\pi}} e^{-ipkd} \frac{\sin(pa)}{pa}$$
Now apply linearity. You want the Fourier transform of
$$\sum_{k=-N}^{N}f_{kd}(x)$$
which is
$$\sum_{k=-N}^{N}\hat{f_{kd}}(p) = \sum_{k=-N}^{N} \sqrt{\frac{2}{\pi}} e^{-ipkd} \frac{\sin(pa)}{pa}$$
Can you see how to simplify this?
I've figured it out! Thanks for all your help, much appreciated!
 
  • #6
I think the formula your lecturer meant is
$$z^{-N} + z^{-(N-1)} + z^{-(N-2)} + \cdots + z^{-1} + 1 + z + \cdots + z^{N-1} + z^{N} = \frac{z^{-(N+1/2)} - z^{N + 1/2}} {z^{-1/2}-z^{1/2}}$$
This can be derived as follows. We can write the left hand side more compactly as
$$\sum_{k=-N}^{N}z^{k}$$
Now introduce the change of variable ##m = k + N## to rewrite the sum as
$$\begin{aligned}
\sum_{m=0}^{2N}z^{m-N} &= z^{-N}\sum_{m=0}^{2N}z^m \\
\end{aligned}$$
Do you see what to do next?

Then, assuming you have established the formula
$$\sum_{k=-N}^{N}z^{k} = \frac{z^{-(N+1/2)} - z^{N + 1/2}} {z^{-1/2}-z^{1/2}}$$
you can apply it to your situation by setting ##z = e^{-ipt}## and simplifying the resulting right hand side.
 

1. What is the Fourier transform of a function?

The Fourier transform is a mathematical operation that decomposes a function into its constituent frequencies. It represents the function as a combination of sine and cosine waves of different frequencies and amplitudes.

2. How is the Fourier transform calculated?

The Fourier transform is calculated by integrating the function with respect to frequency over the entire range of frequencies. This results in a complex-valued function, known as the Fourier spectrum, which contains information about the amplitudes and phases of the constituent frequencies.

3. What is the use of the Fourier transform in science?

The Fourier transform is used in a wide range of scientific fields, including signal processing, image and sound analysis, and quantum mechanics. It allows us to analyze and manipulate signals in the frequency domain, providing insights into the underlying physical processes.

4. What are the properties of the Fourier transform?

The Fourier transform has several important properties, including linearity, time shifting, frequency shifting, and convolution. These properties make it a powerful tool for analyzing and manipulating signals in different domains.

5. Can any function be represented by its Fourier transform?

Yes, any function that satisfies certain mathematical conditions, known as the Dirichlet conditions, can be represented by its Fourier transform. These conditions ensure that the function is well-behaved and has a finite number of discontinuities.

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