How to Calculate Power Spectral Density S(jw) of a Signal?

In summary, the individual is trying to find a way to calculate power spectral density, but is having difficulty because of some maths and range issues. The individual also mentions that there may be another way to do the calculation, but does not provide more information.
  • #1
evol_w10lv
71
0

Homework Statement


First of all, I have to calculate power spectral density S(jw) of this signal:
q7i2xd1mawd8yrpvz4kk.png

It looks something like that:
patgymqa16sv87b2ajrj.png

t>=0


Homework Equations





The Attempt at a Solution


It seems to me, that I can't use this standart formula:
9qh6yuco66x2t4dzyqbe.png


So.. I see that there is signal multiplication- exponent and sinus, but still not clear how to get spectral density S(jw).
Any ideas?
 
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  • #2
This problem is definitely not in my comfort zone, but why can't you use$$
\sin(wt) = \frac{e^{iwt}-e^{-iwt}}{2i}$$and use the standard formula with just exponentials?
 
  • #3
I have got limit from 0 to infinity. I guess, when I use infinity as limit, then I will get e^(inf) which is infinity and then all solution will be infinity. But speaking about the task.. in my opinion there have to use other method, but I don't know which.
 
  • #4
But your ##S(t)## has ##e^{-at}## in it. If ##a## is large enough, won't that help you at your ##\infty## limits? I haven't worked it out because that's your job. Have you actually tried it? And your graphic shows only for ##t>0##.
 
  • #5
Also I noticed, that we can't use the same "w" in exponent and sinus.
So, when I use this formula, then I get:
0iqnd8kzk3q2qy6xq.png

But what about range? It's from 0 to infinity, but I still don't understand some maths there. I guess, that when limit is 0, than all equation is 0. But what about infinity?
-U*exp(-t*(a+jw)) = -U [when t=inf]
What is cos(t*w0) and sin(t*w0), when t=inf?
 
  • #6
evol_w10lv said:
Also I noticed, that we can't use the same "w" in exponent and sinus.
So, when I use this formula, then I get:
0iqnd8kzk3q2qy6xq.png

But what about range? It's from 0 to infinity, but I still don't understand some maths there. I guess, that when limit is 0, than all equation is 0.

Why do you guess everything is zero? Did you try it?

But what about infinity?
-U*exp(-t*(a+jw)) = -U [when t=inf]
What is cos(t*w0) and sin(t*w0), when t=inf?

What happens to terms like ##e^{-at}\sin(\omega_0 t)## and terms like ##e^{-at}e^{iwt}## when ##t\to\infty##?
 
  • #7
It's not 0, I tried it, but I found out, that we can't just use standart formula, because a sine wave spectral density has only a delta function at the carrier frequency since the signal contains just
one spectral component namely the carrier frequency.
So I need to do this task in other way. I think using this property:
kn139p2flydp5413iik9.png


When I try it with standart formula:
n5mf96e2jza6t4iutbs.png

But it don't give same signal as it was at the beggining, when I use inverse formula:
wr63gmt9eetzr3f4m8uj.png
 
  • #8
1. What is the Fourier integral X(f) of this time function x(t)?
2. What is the energy represented in x(t)? Hint: invoke Parseval's theorem.
3. What is the formula for power, given X(f)? Recall that power = energy averaged over time.
4. What then is the power spectrum G(f)? 2G(f), when integrated over all frequencies, gives you the power.

Note that I'm using only positive frequencies, that's why it's 2G(f) instead of G(f). That factr also impacts your computation of time-averaged energy.
 
  • #9
evol_w10lv;4572587 When I try it with standard formula: [ATTACH=full said:
165412[/ATTACH]



I will let Rude man take it from here because he obviously knows about this stuff.

But do you not see that the "standard formula" you mention above is the answer you get when you work out the integral you started with?
 

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  • #10
LCKurtz said:
But do you not see that the "standard formula" you mention above is the answer you get when you work out the integral you started with?

Are you saying, that it should be the correct answer?
n5mf96e2jza6t4iutbs.png

And here is the way, how I get it, if it's necessary:
73wyzwuivwffq02hpn_thumb.jpg

But, when I use this formula:
wr63gmt9eetzr3f4m8uj.png

(inverse formula of spectral density or inverse Fourier trasnsform formula)
I should get back s(t) as it was at the beginng, but it's not. Or maybe I can't use inverse formula in this case?
If we are speaking about requirement for the integral to converge, I'm not convinced about this method, because I'm not sure wheather this 'infinity' criterie is acceptable or not when we got sinus. I knpw that pure sine in the time domain evaluates to a delta function in the frequency domain, but in my case it is combinated with exponential term. It should leads to a spread of the energy in the frequency domain, as one conversant person said, but still I'm confused.

rude man said:
1. What is the Fourier integral X(f) of this time function x(t)?
2. What is the energy represented in x(t)? Hint: invoke Parseval's theorem.
3. What is the formula for power, given X(f)? Recall that power = energy averaged over time.
4. What then is the power spectrum G(f)? 2G(f), when integrated over all frequencies, gives you the power.
1. If it's angular freqvency, than formula is almost the same as PSD forumula:
aw0janux4rttm34gkb.png

And then result shuld be the same:
Result without limits:
0iqnd8kzk3q2qy6xq.png

Result with limits (0..inf):
n5mf96e2jza6t4iutbs.png

But same understanting, which I mentioned to LCKurtz.
Maybe I have to use two Fourier function multiplication?
Can you explain something more to clear my doubts?
Then I'll continue the task, considering your points. And at the end, as I understand, after I use Parseval's theorem, to get power spectral density, I only need to square the modulus?
 
Last edited:
  • #11
evol_w10lv said:
1. If it's angular freqvency, than formula is almost the same as PSD forumula:
aw0janux4rttm34gkb.png

PSD of x(t) is not simply the Fourier transform of x(t). Power immediately implies some kind of squared function. (For example, power dissipated in a 1 ohm resistor = V2, V is volts). So my hint is to consider squaring X(f), which is energy (Parseval), then finding the total energy divided by the total time which is the average power.

PSD integrated from f = -∞ to +∞ is the average power in the signal. So two times the integral of PSD over the positive frequency range of interest is also the average power in the signal. That should get you the correct expression for PSD.

P.S. I like to use f instead of ω.
So my Fourier transform is X(f) = ∫x(t)exp(-jwt)dt with ω = 2πf and working with f from then on.
 
  • #12
I think, that we are speaking about different things. My fault.
And I don't have to find PSD, if it's:
a87ad2211534759928fb1955e31e2d2d.png

And I don't have to find energy spectral density neither:
c13c0db8c0bdbbeb25ff1a20f271a010.png

It was non-understanding with language and translation..
So.. I still don't know, how exactly I should say, but it's like Fourier transform. I have to calculate function in frequency domain.
For example:
041sk4atntuz3liixxi.png

I have to calculate my task like in this example.
And after that, also there are few extra tasks linked with S(jw), but now.. it means that it is Fourier transform and this is the answer of my s(t)?
n5mf96e2jza6t4iutbs.png
 
  • #13
You never responded to my questions, quoted below, in post #4.

LCKurtz said:
What happens to terms like ##e^{-at}\sin(\omega_0 t)## and terms like ##e^{-at}e^{iwt}## when ##t\to\infty##?

evol_w10lv said:
and this is the answer of my s(t)?
n5mf96e2jza6t4iutbs.png

So I don't know if you understand or not why that is the answer.
 
  • #14
LCKurtz said:
But your ##S(t)## has ##e^{-at}## in it. If ##a## is large enough, won't that help you at your ##\infty## limits? I haven't worked it out because that's your job. Have you actually tried it? And your graphic shows only for ##t>0##.

In that case it gives 0 and then all part f(inf) gives 0.
There was doubts in my mind about Dirichlet's condition and sin(inf*w), but of course.. e^(-a*inf)=0, then it not matters.
Now it's clear. Thanks.
 
  • #15
OK, if all you need is the Fourier transform of your time function then follow the advice in posts 2 and 4.
The Fourier transform definitely exists.
 
  • #16
Also I have to calculate amplitude spectrum from S(jw).
jwhar9akwy1dpxtykums.png

But it's quite complicated s(jw) to separate real and imaginary part.
j9cdqesqm6grxogu51f.png

Are there is no easiest method?
So here is easy example:
q566kxv9ia5w5r1kj7z.png

What's the way in my S(jw) case? Must use this method?
 
  • #17
I agree, the math is messy.

You should also consider that mutliplication in the time domain = convolution in the frequency domain.
 
  • #18
Task is done. Thanks.
 

Related to How to Calculate Power Spectral Density S(jw) of a Signal?

What is the spectral density of a signal?

The spectral density of a signal is a measure of how much energy is contained in different frequency components of the signal. It describes the distribution of power or energy of a signal across different frequencies.

Why is the spectral density of a signal important?

The spectral density of a signal is important because it provides valuable information about the characteristics of the signal. It can help in understanding the underlying processes that generate the signal and can be used for signal processing, filtering, and noise reduction.

How is the spectral density of a signal calculated?

The spectral density of a signal is typically calculated using the Fourier transform. This involves breaking down a signal into its frequency components and analyzing the amplitude and phase of each component. It can also be calculated using other methods, such as the autocorrelation function or the power spectral density function.

What is the difference between power spectral density and spectral density?

Power spectral density (PSD) and spectral density are often used interchangeably, but there is a subtle difference between the two. While spectral density describes the distribution of energy across frequencies, PSD describes the distribution of power across frequencies. In other words, PSD takes into account the amplitude and frequency of the signal, whereas spectral density only considers the frequency components.

How is the spectral density of a signal used in practical applications?

The spectral density of a signal has various applications in fields such as signal processing, telecommunications, and data analysis. It can be used for filtering, noise reduction, and feature extraction from signals. In telecommunications, spectral density is used to optimize bandwidth and improve signal transmission. It is also used in data analysis to identify patterns and trends in time series data.

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