Fourier Transform with inverse

In summary, the conversation is about a question regarding an inverse Fourier problem and the integration of the Sinc function. The author goes through the calculations step-by-step and provides a solution to the problem. The person asking the question is interested in finding another way to integrate the Sinc function. The author did not do an explicit integration, but rather used standard theorems about Fourier transforms and their inverses. The person asking the question is also referred to an article that explains Fourier transforms in a different way.
  • #1
Aows

Homework Statement


Q/ in this inverse Fourier problem, how did he come with the results of integration of (Sinc) function and how did he come up with those results of integration with the inverse part (as in the attached picture)
here is the problem:
https://i.imgur.com/Ir3TQIN.png

Homework Equations


all equation needed are in the relevant picture

The Attempt at a Solution


tried a lot until the integration of the sinc and results are not the same.
 
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  • #2
Aows said:

Homework Statement


Q/ in this inverse Fourier problem, how did he come with the results of integration of (Sinc) function and how did he come up with those results of integration with the inverse part (as in the attached picture)
here is the problem:
https://i.imgur.com/Ir3TQIN.png

Homework Equations


all equation needed are in the relevant picture

The Attempt at a Solution


tried a lot until the integration of the sinc and results are not the same.

The author goes through the calculations step-by-step. Which parts do you disagree with, and why?

Note: the author makes some rather obvious "blunders", but if you know calculus you should be able to fix those up for yourself, without help from us. The final answer is correct.
 
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  • #3
Ray Vickson said:
The author goes through the calculations step-by-step. Which parts do you disagree with, and why?

Note: the author makes some rather obvious "blunders", but if you know calculus you should be able to fix those up for yourself, without help from us. The final answer is correct.
yes true Dr. Ray,
my question is : is it possible to get the integration of Sinc function in another way ?
 
  • #4
Aows said:
yes true Dr. Ray,
my question is : is it possible to get the integration of Sinc function in another way ?

No, that was NOT your question. You asked

"Q/ in this inverse Fourier problem, how did he come with the results of integration of (Sinc) function and how did he come up with those results of integration
with the inverse part (as in the attached picture)"

You were very clearly saying that you did not understand what the author was doing; you were not asking about doing it another way.
 
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  • #5
Ray Vickson said:
No, that was NOT your question. You asked

"Q/ in this inverse Fourier problem, how did he come with the results of integration of (Sinc) function and how did he come up with those results of integration
with the inverse part (as in the attached picture)"

You were very clearly saying that you did not understand what the author was doing; you were not asking about doing it another way.
Hello Dr.Ray,
i manages to solve the question later, but my last question was about finding another way of integrating the (Sinc) function if possible .

and thanks for you valuable notes and help from the beginning
 
  • #7
Aows said:
Hello Dr.Ray,
i manages to solve the question later, but my last question was about finding another way of integrating the (Sinc) function if possible .

and thanks for you valuable notes and help from the beginning
Aows said:
Hello Dr.Ray,
i manages to solve the question later, but my last question was about finding another way of integrating the (Sinc) function if possible .

and thanks for you valuable notes and help from the beginning

I don't think he did an explicit integration; rather, he (probably) used some standard theorems about Fourier transforms and their inverses. For example, if you use a Fourier transform defined by
$$g(\theta) = ({\cal F}f)(\theta) \equiv \int_{-\infty}^{\infty} f(t) e^{-2 \pi i \theta t} \, dt, $$
then for piecewise smooth ## f ## which, together with all its derivatives, decay quickly as ##t \to \pm \infty##, we have
$$ ({\cal F}^{-1} g) (t) \equiv
\int_{-\infty}^{\infty} g(\theta) e^{+2 \pi i \theta t} \, d \theta = \frac{1}{2} \left[ f(t-) + f(t+)\right],$$
where ##f(t-)## and ##f(t+)## are the left-hand limits and right-hand limits of ##f(u)## as ##u \to t##.

In other words, at points ##t## where ##f(t)## is continuous we have ##({\cal F}^{-1} g) (t) = f(t)##, but at a point ##t## where ##f## has a "jump discontinuity" the inverse F.T. equals the average of the two ## f ## values on either side of the jump.

The ##f(t)## in your problem has jump discontinuities at ##t=-1## and ##t=1## but is continuous everywhere else (and it certainly is damped at large valus of ##|t|##), so that gives the result, up to some constants. The author uses a different definition/normalization for the Fourier transform (using ##i \omega t## instead of ##2 \pi i \theta t## in the exponent), so the inverse will have an extra multiplicative constant in it; you can work out the details for yourself.

Note: the theorem I cited above is not trivial, and may not be proved at all in an introductory course or an "engineering math" or "math for physics course". A brief proof outline is given in
https://en.wikipedia.org/wiki/Fourier_inversion_theorem
but it is very short and leaves out a lot of details for the reader to fill in if he/she can.
A longer and more detailed proof is in https://www.ima.umn.edu/~miller/fouriertransform.pdf
https://www.ima.umn.edu/~miller/fouriertransform.pdf
but it is still not easy.
 
Last edited:
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  • #9
Ray Vickson said:
I don't think he did an explicit integration; rather, he (probably) used some standard theorems about Fourier transforms and their inverses. For example, if you use a Fourier transform defined by
$$g(\theta) = ({\cal F}f)(\theta) \equiv \int_{-\infty}^{\infty} f(t) e^{-2 \pi i \theta t} \, dt, $$
then for piecewise smooth ## f ## which, together with all its derivatives, decay quickly as ##t \to \pm \infty##, we have
$$ ({\cal F}^{-1} g) (t) \equiv
\int_{-\infty}^{\infty} g(\theta) e^{+2 \pi i \theta t} \, d \theta = \frac{1}{2} \left[ f(t-) + f(t+)\right],$$
where ##f(t-)## and ##f(t+)## are the left-hand limits and right-hand limits of ##f(u)## as ##u \to t##.

In other words, at points ##t## where ##f(t)## is continuous we have ##({\cal F}^{-1} g) (t) = f(t)##, but at a point ##t## where ##f## has a "jump discontinuity" the inverse F.T. equals the average of the two ## f ## values on either side of the jump.

The ##f(t)## in your problem has jump discontinuities at ##t=-1## and ##t=1## but is continuous everywhere else (and it certainly is damped at large valus of ##|t|##), so that gives the result, up to some constants. The author uses a different definition/normalization for the Fourier transform (using ##i \omega t## instead of ##2 \pi i \theta t## in the exponent), so the inverse will have an extra multiplicative constant in it; you can work out the details for yourself.

Note: the theorem I cited above is not trivial, and may not be proved at all in an introductory course or an "engineering math" or "math for physics course". A brief proof outline is given in
https://en.wikipedia.org/wiki/Fourier_inversion_theorem
but it is very short and leaves out a lot of details for the reader to fill in if he/she can.
A longer and more detailed proof is in
https://www.ima.umn.edu/~miller/fouriertransform.pdf
but it is still not easy.
Thanks indeed Dr.Ray for your explanation, but can you explain more the part where the F(1) and f(-1) why they both divided by two ?
 
  • #10
Aows said:
Thanks indeed Dr.Ray for your explanation, but can you explain more the part where the F(1) and f(-1) why they both divided by two ?

I just did that, in detail. Read my answer again, and compute the results for your function
$$
f(t) = \begin{cases} 0, & \;\; t < -1 \\
1 , & -1 \leq t \leq 1 \\
0 , &\;\; t > 1
\end{cases}
$$
 
Last edited:
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Related to Fourier Transform with inverse

1. What is Fourier Transform with inverse?

The Fourier Transform with inverse is a mathematical operation used to convert a signal from its original domain (usually time or space) to a representation in the frequency domain. This allows for the analysis of the signal's frequency spectrum.

2. How does the Fourier Transform with inverse work?

The Fourier Transform with inverse uses a complex mathematical formula to break down a signal into its constituent frequencies. It decomposes the signal into a series of sine and cosine waves with different frequencies, amplitudes, and phases, which can then be analyzed separately.

3. What is the difference between the Fourier Transform and the inverse Fourier Transform?

The Fourier Transform converts a signal from the time or space domain to the frequency domain, while the inverse Fourier Transform converts it back from the frequency domain to the time or space domain. Essentially, the Fourier Transform with inverse is a reversible process.

4. What are the applications of Fourier Transform with inverse in science?

The Fourier Transform with inverse has many applications in science, including signal processing, image and audio compression, and data analysis. It is also used in fields such as physics, engineering, and economics to analyze and understand complex systems and phenomena.

5. Are there any limitations to the Fourier Transform with inverse?

Yes, there are some limitations to the Fourier Transform with inverse. It assumes that the signal is periodic, meaning that it repeats itself infinitely. It also assumes that the signal is continuous, meaning that it has no gaps or disruptions. In reality, most signals are not perfectly periodic or continuous, so the Fourier Transform with inverse may not provide an accurate representation. Additionally, the Fourier Transform with inverse is sensitive to noise, which can affect the accuracy of the results.

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