Calculating Fourier Transform on TI-89 for Non-Integrable Functions?

In summary: The answer given in the book is pi*e^abs(w). One of them is right. or maybe both of them are right?The answer given in the book is pi*e^abs(w).
  • #1
kolycholy
39
0
how would i calculate Fourier transform of functions such as 1/(1+t^2)?
because if you try to integrate the product of the above function and e^(-jxt), you would realize it's nonintegrable or something
at least my ti-89 does not calculate it for me.
any other way?
 
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  • #2
Integration by parts perhaps, although I can imagine that getting very messy very fast. Is it possible that you could integrate numerically? I think that would at least work in finding a Fourier series, but I'm not certain.
 
  • #3
Mathematica can calculate the Fourier transform, according to that it's sqrt(pi/2)/e^abs(w)

however, I'm not completely sure how you would go about doing it manually. I would agree that integration by parts is the first step to try.
 
  • #4
jbusc said:
Mathematica can calculate the Fourier transform, according to that it's sqrt(pi/2)/e^abs(w)

however, I'm not completely sure how you would go about doing it manually. I would agree that integration by parts is the first step to try.

the answer given in the book is pi*e^abs(w).
One of them is right. or maybe both of them are right?
 
  • #5
You would need to solve this integral via contour integration (at least this is the first thing that comes to mind). Have a look on google for "functions of a complex variable" or "residue theorem" or simply "contour integral" or something like this. Anyway, contour integration allows you evaluate these types of integrals pretty quickly.

By the way the answers stated here differ by a factor of [itex]\pi^{1/2}[/itex]. This is probably because one of you is using the forward Fourier transform as being defiend with a prefactor of [itex]1/2\pi[/itex] and the backward transform having a prefactor of 1, while the other one is using the prefactor [itex][1/2\pi]^{1/2}[/itex] for both the forward and backward transforms.
 
  • #7
Hi George, thanks for the thread.
I should say that in the post on this thread, the contour you pick (semicircle in the upper or lower half plane) is determined by the sign of [itex]\omega[/itex].
 

Related to Calculating Fourier Transform on TI-89 for Non-Integrable Functions?

1. What is a Fourier transform and how does it work on the TI-89 calculator?

The Fourier transform is a mathematical tool used to decompose a signal into its individual sine and cosine components. On the TI-89 calculator, the Fourier transform can be performed using the built-in function "fft()". This function takes in a list of data points and outputs the corresponding frequency spectrum.

2. Can the TI-89 calculator handle complex numbers in the Fourier transform?

Yes, the TI-89 calculator can handle complex numbers in the Fourier transform. The "fft()" function has an optional argument that allows the user to specify whether the input data is real or complex. By default, it assumes the data is real.

3. Are there any limitations to using the Fourier transform on the TI-89 calculator?

One limitation of using the Fourier transform on the TI-89 calculator is that the input data must be in the form of a list. This means that the data points must be equally spaced and there cannot be any gaps in the data. Additionally, the "fft()" function can only handle a maximum of 4096 data points.

4. Can the Fourier transform be used to analyze non-periodic signals on the TI-89 calculator?

Yes, the Fourier transform can be used to analyze non-periodic signals on the TI-89 calculator. However, the resulting frequency spectrum may not be as accurate as it would be for a periodic signal. This is because the Fourier transform assumes the signal repeats infinitely, which is not the case for non-periodic signals.

5. How can I interpret the results of the Fourier transform on the TI-89 calculator?

The results of the Fourier transform on the TI-89 calculator will give you information about the frequency components present in the input signal. The magnitude of each component represents the amplitude of that particular frequency, while the phase angle represents the offset or delay of that frequency. The frequency with the highest magnitude is considered the dominant frequency in the signal.

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