How to calculate this inverse Fourier Transform?

In summary: I? I have no idea what I'm doing anymore :rofl:OK, I'm pretty sure I'm doing something wrong, but I'll show you what I've done so far. So, I've converted the rectangular coordinates to polar coordinates, making the fractions:##\frac{180.2\angle 2.70^\circ}{1680.02\angle 0.29^\circ} = \frac{181.4 e^{j2.70^\circ}}{1680.13 e^{j0.29^\circ}}####\frac{180.2\angle -2.70^\circ}{1680.02\angle -0.29^\circ} = \frac{
  • #1
Nat3
69
0

Homework Statement



Take the inverse Fourier Transform of

[tex]5[\delta(f+100)+\delta(f-100)]\bigg(\frac{180+j2\pi f*0.0135}{1680+j2\pi f*0.0135}\bigg)[/tex]

Homework Equations



[tex]g(t)=\int_{-\infty}^{\infty} G(f)e^{j2\pi ft}dt[/tex]

The Attempt at a Solution



[tex]g(t)=\int_{-\infty}^{\infty} 5[\delta(f+100)+\delta(f-100)]\bigg(\frac{180+j2\pi f*0.0135}{1680+j2\pi f*0.0135}\bigg) e^{j2\pi ft}dt[/tex]

My professor gave the hint that the dirac delta sampling property can be used, but I don't see how since I'm taking the inverse Fourier Transform and not just a regular integral.

I've been reading about the different properties of the FT and dirac delta function, but simply can't figure out how to proceed. Any suggestions?
 
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  • #2
?? The inverse Fourier Transform is a "regular integral"! And the "Dirac delta sampling property" is that [itex]\int_{-\infty}^\infty \delta(x- a)f(x)dx= f(a)[/itex]. That should make this problem easy.
 
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  • #3
Ah.. I'm not sure what I was thinking, lol :-)

OK, so having this equation:

[tex]g(t)=\int_{-\infty}^{\infty} 5[\delta(f+100)+\delta(f-100)]\bigg(\frac{180+j2\pi f*0.0135}{1680+j2\pi f*0.0135}\bigg) e^{j2\pi ft}dt[/tex]

When using the sifting/sampling property of the Dirac Delta function:

[tex]\int_{-\infty}^\infty \phi (t) \delta(t - T)dt = \phi (T)[/tex]

Should I replace [itex]f[/itex] or [itex]t[/itex] in the above equation with [itex]\pm 100[/itex]? It seems like I should replace the [itex]f[/itex]:

[tex]g(t)=5\bigg (\frac{180+j2\pi f*0.0135}{1680+j2\pi f*0.0135}\bigg) e^{j2\pi ft} \bigg |_{f=100}+5\bigg (\frac{180+j2\pi f*0.0135}{1680+j2\pi f*0.0135}\bigg) e^{j2\pi ft} \bigg |_{f=-100}[/tex]

[tex]g(t)=5\bigg (\frac{180+j2\pi *1.35}{1680+j2\pi *1.35}\bigg) e^{j200\pi t}+5\bigg (\frac{180-j2\pi *1.35}{1680-j2\pi *1.35}\bigg) e^{-j200\pi t}[/tex]

But I'm not sure if that's correct?
 
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  • #4
Does anyone know if what I did is correct? Operating under that assumption, I tried converting the rectangular coordinate complex numbers to polar form:

[tex]g(t)=5\bigg (\frac{180.2\angle 2.70^\circ}{1680.02\angle 0.29^\circ}\bigg) e^{j200\pi t}+5\bigg (\frac{180.2\angle -2.70^\circ}{1680.02\angle -0.29^\circ}\bigg) e^{-j200\pi t}[/tex]

[tex]g(t)=5\bigg (\frac{180.2\angle 2.70^\circ}{1680.02\angle 0.29^\circ}\bigg) e^{j200\pi t}+5\bigg (\frac{180.2\angle -2.70^\circ}{1680.02\angle -0.29^\circ}\bigg) e^{-j200\pi t}[/tex]

[tex]g(t)=5(0.11\angle 2.41^\circ) e^{j200\pi t}+5(0.11\angle -2.41^\circ) e^{-j200\pi t}[/tex]

I think I might be doing something wrong though, because I think the answer is supposed to work out to be:

[tex]1.1\cos(2\pi (100)t+2.41^\circ)[/tex]
 
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  • #5
Nat3 said:
Ah.. I'm not sure what I was thinking, lol :-)

OK, so having this equation:

[itex]g(t)=\int_{-\infty}^{\infty} 5[\delta(f+100)+\delta(f-100)]\bigg(\frac{180+j2\pi f*0.0135}{1680+j2\pi f*0.0135}\bigg) e^{j2\pi ft}dt[/itex]
The integral should be with respect to ##f##, not ##t##.

When using the sifting/sampling property of the Dirac Delta function:

[itex]\int_{-\infty}^\infty \phi (t) \delta(t - T)dt = \phi (T)[/itex]

Should I replace [itex]f[/itex] or [itex]t[/itex] in the above equation with [itex]\pm 100[/itex]? It seems like I should replace the [itex]f[/itex]:

[itex]g(t)=5\bigg (\frac{180+j2\pi f*0.0135}{1680+j2\pi f*0.0135}\bigg) e^{j2\pi ft} \bigg |_{f=100}+5\bigg (\frac{180+j2\pi f*0.0135}{1680+j2\pi f*0.0135}\bigg) e^{j2\pi ft} \bigg |_{f=-100}[/itex]

[itex]g(t)=5\bigg (\frac{180+j2\pi *1.35}{1680+j2\pi *1.35}\bigg) e^{j200\pi t}+5\bigg (\frac{180-j2\pi *1.35}{1680-j2\pi *1.35}\bigg) e^{-j200\pi t}[/itex]

But I'm not sure if that's correct?
That's right.
 
  • #6
Nat3 said:
Does anyone know if what I did is correct? Operating under that assumption, I tried converting the rectangular coordinate complex numbers to polar form:

[itex]g(t)=5\bigg (\frac{180.2\angle 2.70^\circ}{1680.02\angle 0.29^\circ}\bigg) e^{j200\pi t}+5\bigg (\frac{180.2\angle -2.70^\circ}{1680.02\angle -0.29^\circ}\bigg) e^{-j200\pi t}[/itex]

[itex]g(t)=5\bigg (\frac{180.2\angle 2.70^\circ}{1680.02\angle 0.29^\circ}\bigg) e^{j200\pi t}+5\bigg (\frac{180.2\angle -2.70^\circ}{1680.02\angle -0.29^\circ}\bigg) e^{-j200\pi t}[/itex]

[itex]g(t)=5(0.11\angle 2.41^\circ) e^{j200\pi t}+5(0.11\angle -2.41^\circ) e^{-j200\pi t}[/itex]

I think I might be doing something wrong though, because I think the answer is supposed to work out to be:

[itex]1.1\cos(2\pi (100)t+2.41^\circ)[/itex]
You're right so far. You just have to keep going with the simplification.

It might be simpler if you note at the start that the two terms are conjugates and use the fact that ##z+\bar{z} = 2\text{Re}(z)##.
 
  • #7
Hmm... I've been trying to simplify it and am not sure how to proceed. I tried changing the polar portion to ##\cos## and using Euler's identity to change the exponentials to ##\cos## and ##\sin##, which gives:

##g(t) = 5[0.11\cos(\omega t + 2.41^\circ)[\cos(200\pi t) + j\sin(200\pi t)] + 0.11\cos(\omega t - 2.41^\circ)[\cos(200\pi t) - j\sin(200\pi t)]]##

But I feel like I'm on the wrong track here. If I multiply that out then it becomes a mess. Did I go in the wrong direction with this?

Really appreciate your help :)
 
  • #8
Hint: ##0.11\angle 2.41^\circ = 0.11 e^{j 2.41^\circ}##
 
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  • #9
vela said:
Hint: ##0.11\angle 2.41^\circ = 0.11 e^{j 2.41^\circ}##

Did you by any chance mean:

##0.11\angle 2.41^\circ = Re(0.11 e^{j 2.41^\circ})##? Otherwise, I'm really confused :smile:

Because:

##0.11\angle 2.41^\circ = 0.11\cos(\omega t + 2.41^\circ)##

And:

##0.11 e^{j 2.41^\circ} = 0.11\cos(\omega t + 2.41^\circ) + j0.11\sin(\omega t + 2.41^\circ)##
 
  • #10
Nat3 said:
$$g(t)=5 \left( \frac{180.2\angle 2.70^\circ}{1680.02\angle 0.29^\circ}\right) e^{j200\pi t} + 5 \left( \frac{180.2\angle {-2.70}^\circ}{1680.02\angle {-0.29}^\circ}\right) e^{-j200\pi t}$$
What I mean is express the fractions in polar form, i.e. ##re^{j\theta}##.
 
  • #11
vela said:
What I mean is express the fractions in polar form, i.e. ##re^{j\theta}##.

Like this?

[tex]g(t)=5\bigg (\frac{180.2\angle 2.70^\circ}{1680.02\angle 0.29^\circ}\bigg) e^{j200\pi t}+5\bigg (\frac{180.2\angle -2.70^\circ}{1680.02\angle -0.29^\circ}\bigg) e^{-j200\pi t}[/tex]

[tex]g(t)=5(0.11\angle 2.41^\circ) e^{j200\pi t}+5(0.11\angle -2.41^\circ) e^{-j200\pi t}[/tex]

[tex]g(t)=5Re(0.11e^{j2.41^\circ})e^{j200\pi t} + 5Re(0.11e^{-j2.41^\circ})e^{-j200\pi t}[/tex]

I can't combine the exponentials being multiplied together (because one is only the real part), can I?
 
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  • #12
Nat3 said:
$$g(t)=5 \left( \frac{180+j2\pi *1.35}{1680+j2\pi *1.35} \right) e^{j200\pi t} + 5 \left(\frac{180-j2\pi *1.35}{1680-j2\pi *1.35}\right) e^{-j200\pi t}$$
OK, let's back up one more step. Convert the complex numbers from rectangular to polar form then simplify.
 
  • #13
Nat3, I admire that you write all these equations in LaTeX. But one hint: if you want your formula to have its own line, then you should use tex, and not itex. I have changed this for you in your posts. The result really is a lot easier on the eyes. Check the difference between post 4 and the quoted part in post 5, for example.
 

1. How do I calculate the inverse Fourier Transform for a given signal?

To calculate the inverse Fourier Transform for a signal, you can use the formula: x(t) = ∫-∞+∞X(ω)ejωtdω, where x(t) is the original signal and X(ω) is the Fourier Transform of the signal. This integral can be evaluated using various mathematical techniques, such as integration by parts or substitution.

2. What is the significance of the inverse Fourier Transform in signal processing?

The inverse Fourier Transform is a key tool in signal processing as it allows us to convert a signal from the frequency domain to the time domain. This helps in analyzing and understanding the behavior of a signal over time, and also allows for various signal processing techniques, such as filtering and noise removal, to be applied.

3. Can the inverse Fourier Transform be calculated using software or do I need to do it manually?

Yes, the inverse Fourier Transform can be calculated using software, such as MATLAB or Python libraries like NumPy and SciPy. These software have built-in functions that can directly calculate the inverse Fourier Transform of a given signal, making the process much faster and more accurate.

4. Are there any limitations to calculating the inverse Fourier Transform?

One limitation of calculating the inverse Fourier Transform is that the signal must have a Fourier Transform. This means that the signal must be finite and have a well-defined frequency spectrum. Additionally, some signals may have complex or non-analytic Fourier Transforms, making it difficult to calculate the inverse Fourier Transform.

5. Can the inverse Fourier Transform be used for any type of signal, or only specific types?

The inverse Fourier Transform can be used for a wide range of signals, including continuous-time and discrete-time signals, periodic and non-periodic signals, and even multi-dimensional signals. However, some signals may require additional techniques, such as the Laplace Transform, to accurately calculate their inverse Fourier Transform.

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