Fourier Transform of a Gaussian With Non-Zero Mean

malevolence19
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Homework Statement


I am looking at finding the Fourier transform of:
f(t)=\exp \left[ \frac{-(t-m)^2}{2 \sigma^2}\right]

Homework Equations



\hat{f}(t)=\frac{1}{\sqrt{2 \pi}} \int_{-\infty}^{\infty} f(t) e^{-i \omega t} dt

The Attempt at a Solution


I did it a little differently that my professor suggested. He said use taylor series but when I do that I end up getting a triple sum (2 from the exponentials and 1 coming from an (x+m)^j; so I used binomial expansion) so I did it the traditional way you deal with gaussians: complete the square.

I combined the exponentials, completed the square and end up with an answer that looks like:
\hat{f}(t)=\frac{1}{2 \sigma}e^{-(\frac{\sigma^2 \omega^2}{2}+i \sigma \omega)}
But wolfram has this:
http://www.wolframalpha.com/input/?i=fourier+transform+of+e%5E%28-%28t-m%29%5E2%2F%282r%5E2%29%29

With r= 2 \sigma^2

I was just wondering if anyone could double check me against wolfram? I can type out steps if needed. This isn't a homework or anything, he just brought it up and I suggested completing the square instead. Apparently this means I have to present it to the class on Monday -.-
 
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Comparing your expression for f(t) with the input to the Fourier transform at the Wolfram link, I'm not sure why you put r = 2\sigma^2 instead of r = \sigma.

Also, check Wolfram's definition of the Fourier transform. It might not include your 1/\sqrt{2\pi} factor. There is no universal consensus regarding this. [edit]: You can see their definition by clicking on the "definition" link. Indeed, their definition omits the 1/\sqrt{2\pi}
 
That's what I meant r=\sigma. I typed it in two different ways and I had them mixed up :/

And omitting the 1/sqrt(2 pi) gives me:
\sqrt{\frac{\pi}{2 \sigma^2}}e^{-(\frac{\sigma^2 \omega^2}{2}+\sigma^2 i \omega)}
They have the sigma in the numerator some how.
 
Ahhhh, nevermind I see it!
 
By the way, you can also solve this problem by using the shift property of the Fourier transform: if \mathcal{F}[f(t)] = \hat{f}(\omega), then \mathcal{F}[f(t-m)] = \hat{f}(\omega)\exp(-im\omega).
 
jbunniii said:
By the way, you can also solve this problem by using the shift property of the Fourier transform: if \mathcal{F}[f(t)] = \hat{f}(\omega), then \mathcal{F}[f(t-m)] = \hat{f}(\omega)\exp(-im\omega).

Thank you. I always forget about these nice shifting formulae.
 
There are two things I don't understand about this problem. First, when finding the nth root of a number, there should in theory be n solutions. However, the formula produces n+1 roots. Here is how. The first root is simply ##\left(r\right)^{\left(\frac{1}{n}\right)}##. Then you multiply this first root by n additional expressions given by the formula, as you go through k=0,1,...n-1. So you end up with n+1 roots, which cannot be correct. Let me illustrate what I mean. For this...
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