What does a fourier transform do?

In summary, the Fourier transform is a mathematical tool that transforms one function into another. It is not a physical transformation and its interpretation depends on the context and form chosen. If the Fourier transform is applied to a velocity-time function, it will result in the frequency domain form of that function. This is useful in fields such as hydrodynamics. The Dirac delta function often appears in these transforms, and its presence can be interpreted as a discrete spectrum of frequencies.
  • #1
member 428835
hey pf!

physically, what does a Fourier transform do? physically what comes out if i put velocity in?

thanks!

josh
 
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  • #2
The Fourier transform is not a physical transformation, it does not do anything physical.

It is a mathematical tool which turns one function into another one.
The interpretation depends on the form of the transform chosen and the context of the calculation.

If you took the Fourier transform of, say, the velocity-time function of some object, then you'd get the frequency domain form of that function. This is something that crops up in hydrodynamics, but you may be able to see the effect better transforming the v(t) function for SHM.
 
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  • #3
Simon Bridge said:
If you took the Fourier transform of, say, the velocity-time function of some object, then you'd get the frequency domain form of that function.

What do you mean By frequency domain with respect to the velocity? I tried reading online sources (and I'll continue to) but if you know perhaps you can save me some time?

Thanks for your help!
 
  • #4
Well v(t) is the velocity in the time domain.

Put v(t)=v.sin(wt) (SHM)
then find V(w), it's forward Fourier transform and see what you get.
 
  • #5
ok, so we have $$F(x) = \int_{-\infty}^{\infty} e^{-i 2 \pi t x} \sin(\omega t) dt$$ there are probably easier ways to integrate, but if we integrate by parts twice, we arrive at $$F(x) = \left. \frac{\omega \cos(\omega t)+2 i x \pi \sin(\omega t)}{e^{-2 i x \pi t}(4 x^2 \pi^2-\omega^2)} \right|_{-\infty}^{\infty}$$ which implies
$$F(x) = -\left. \frac{\omega \cos(\omega t)+2 i x \pi \sin(\omega t)}{e^{-2 i x \pi t}(4 x^2 \pi^2-\omega^2)} \right|_{-\infty}$$ which can be wrote as
$$F(x) = e^{2 i x \pi t} \left. \frac{\omega \cos(\omega t)- 2 i x \pi \sin(\omega t)}{(4 x^2 \pi^2-\omega^2)} \right|_{\infty}$$ from here, if i use lopital's rule twice i will have a bunch of sine and cosine terms in the numerator multiplied by an increasing exponential. won't this diverge?
 
  • #6
Using your notation: $$F(x) = \int_{-\infty}^{\infty} e^{-i 2 \pi t x} \sin(\omega t)\; dt\\
\qquad = \frac{\delta(x-\omega/2\pi)-\delta(x+\omega/2\pi)}{2i}$$

Integrating exponentials is usualy easy - use Euler's formula to convert the sine, then you get a sum of integrals. Apply the integral definition of the Dirac delta function.

Or you can just look it up:
http://en.wikipedia.org/wiki/Fourier_transform#Distributions
 
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  • #7
Simon Bridge said:
Using your notation: $$F(x) = \int_{-\infty}^{\infty} e^{-i 2 \pi t x} \sin(\omega t)\; dt\\
\qquad = \frac{\delta(x-\omega/2\pi)-\delta(x+\omega/2\pi)}{2i}$$

is ##\delta (x)## the dirac delta function? can you explain how you arrived at this?

thanks a ton for helping me!
 
  • #8
joshmccraney said:
is ##\delta (x)## the dirac delta function? can you explain how you arrived at this?

thanks a ton for helping me!

You can just express ##\sin(\omega t)## in terms of exponential functions:

$$\sin(\omega t)=\frac{e^{i\omega t}-e^{-i\omega t}}{2i}$$

Do you see how to arrive at his result now?
 
  • #9
oh man, i didn't even see the bottom of your post! ok, ill give it a whirl.
 
  • #10
joshmccraney said:
oh man, i didn't even see the bottom of your post! ok, ill give it a whirl.
You were probably replying while I was editing my post to be a bit clearer ;)

I had hoped that you would have gone from: ##v(t)=A\sin\omega_0 t## to using:
$$V(\omega)=\frac{1}{\sqrt{2\pi}}\int_{-\infty}^\infty v(t)e^{-i\omega t}\;dt\\
\qquad = A\sqrt{2\pi}\frac{\delta(\omega-\omega_0)-\delta(\omega+\omega_0)}{2i}$$... or you may find it easier to think about ##v(t)=A\cos\omega t## so that ##V(\omega)## is real.

So - back to post #1.
A specific form of your question would be:
"If ##v(t)## tells you how the velocity of an object undergoing SHM changes with time, what does ##V(\omega)## tell you?"

Can you relate the values of V to the motion of the object?
What happens if the motion is a bit more complicated?
 
  • #11
ok simon, so i am on the same page with you now that the Fourier transform over ##v_0 \sin (\omega t)## yields $$F(x) = v_0\frac{\delta(x-\omega/2\pi)-\delta(x+\omega/2\pi)}{2i}$$

but what does this mean? having the dirac delta function without an integral is difficult for me to interpret. can you help?
 
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  • #12
F is basically a distribution - sure.

Notice that w/2pi is the frequency of the oscillations?
Notice that F has dimensions of velocity?

Explore what happens if f(t) is a sum of different-frequency sine waves? Maybe a product of them?

Note: a mathematical operation on a function representing a physical process need not have a pat physical interpretation.

This may help:
https://www.physicsforums.com/showthread.php?t=217204
 
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  • #13
ok. so if i take ##v(t) = v_0 \sin(2\pi t / 2) \sin(2\pi t/3)## then we have a period of ##6## and a frequency of ##1/6##. i notice the ##5/6##, ##-5/6##, ##1/6##, ##-1/6## all show up in a sum of dirac delta functions (the sums and differences of the frequencies of the sine terms). what's happening here?
 
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  • #14
As well as that - what happens to that constant out the front of the Dirac delta functions?
What does it look like is happening? Looks like a discrete spectrum doesn't it?

It is tricky to wrap you mind around what happens when you switch to the frequency domain.
This is why I'm not just telling you.

Sometime's it is clearer - like the Fourier transform of a position wavefunction is the corresponding momentum wavefunction. Wavefunctions are, similarly, best understood in integrals.
 
  • #15
Simon Bridge said:
As well as that - what happens to that constant out the front of the Dirac delta functions?
its looks like this constant is ##v_0 / 2i##

Simon Bridge said:
What does it look like is happening? Looks like a discrete spectrum doesn't it?

yea, some kind of function that's identically zero except at the sums/differences of the sine waves' frequencies.

what's the deal with these sums/differences? i would have thought, since Fourier series decompose functions into fundamental frequencies of sine/cosine waves. perhaps because we have a product and not a sum?
 
  • #16
A standing wave is the sum of two traveling waves, same wavelength and amplitude, going in opposite directions.
So Asin(wt) is made of two plane waves with amplitude A/2 headed in opposite directions.
Alternatvely it is two phasors magnitude A/2 rotating in opposite directions.
The Fourier transform reflects this, which is why it is so useful in signal processing.

When you multiply two sine waves together, you can decompose that into a sum of sine waves.
The argument of the sines involve the sum and difference of the frequencies.
http://en.wikipedia.org/wiki/List_o...#Product-to-sum_and_sum-to-product_identities$$A\sin(\omega_1 t) \sin(\omega_2 t) = \frac{A}{2}\cos (\omega_1-\omega_2)t-\frac{A}{2}\cos(\omega_1+\omega_2)t$$... so you'd expect the Fourier transform to be non-zero at the sum and difference of the sine wave freqencies.
 
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  • #17
oh ok. from eulers identity. thanks!
 
  • #18
you've been a big help!
 
  • #19
No worries - this is something that means different things in different contexts but you should have a better feel for what the transform is doing now. You'll get more when you study distributive integrals and measure theory.
 

1. What is a Fourier transform?

A Fourier transform is a mathematical tool used to decompose a signal into its individual frequency components. It transforms a signal from the time domain to the frequency domain, allowing for the analysis of periodic or non-periodic signals.

2. How does a Fourier transform work?

A Fourier transform works by breaking down a complex signal into simple sine and cosine waves of different frequencies. This is achieved by using complex numbers and integration to convert the signal from the time domain to the frequency domain.

3. What are the applications of a Fourier transform?

A Fourier transform has many applications in various fields such as signal processing, image processing, data compression, and solving differential equations. It is also used in areas like audio and video compression, medical imaging, and speech recognition.

4. 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 also gives the frequency components of a signal, while a Fourier series gives the amplitude and phase of each individual frequency component.

5. What are the limitations of a Fourier transform?

A Fourier transform assumes that the signal is stationary, meaning it does not change over time. It also assumes that the signal is infinite and periodic, which is not always the case in real-world applications. Additionally, it cannot accurately analyze signals with sharp changes or discontinuities.

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