Applying Parseval’s theorem

  • Thread starter MartynaJ
  • Start date
  • Tags
    Theorem
In summary, the conversation discusses the equivalence of two equations related to noise amplitude and the use of Parseval's theorem to determine the power of noise in the frequency domain. The question asks about the relationship between average noise amplitude and the integral of squared noise amplitudes. Using the given information, it is determined that the power of noise in the time domain is proportional to 4 of some arbitrary units and the noise amplitude can be found by solving for the value that makes the equation 4 times larger.
  • #1
MartynaJ
19
1
Homework Statement
You have a signal with a maximum frequency of 40 MHz. The average noise amplitude is 2 mV in the time domain. The noise is uniformly distributed from 0 to 40 MHz in the frequency domain. Now you apply a filter to remove all the frequency components above 10 MHz. What is the average amplitude of the noise in the filtered signal in the time domain?
Relevant Equations
##\int_\infty ^\infty {\left| f(x) \right|}^2 dx=\int_\infty ^\infty {\left| F(u) \right|}^2 du##
Before:
##\int_\infty ^\infty {\left| F_i(u) \right|}^2 du=\int_0 ^{40} a^2 du=40 a^2##

Therefore: ##a^2= \frac{1}{40}\int_\infty ^\infty {\left| F_i(u) \right|}^2 du##

After:
##\int_\infty ^\infty {\left| F_f(u) \right|}^2 du=\int_0 ^{10} a^2 du=10 a^2##

Therefore: ##a^2= \frac{1}{10}\int_\infty ^\infty {\left| F_f(u) \right|}^2 du##

Equating the two equations:
##\frac{1}{40}\int_\infty ^\infty {\left| F_i(u) \right|}^2 du=\frac{1}{10}\int_\infty ^\infty {\left| F_f(u) \right|}^2 du##

Therefore:
##\int_\infty ^\infty {\left| F_i(u) \right|}^2 du=4\int_\infty ^\infty {\left| F_f(u) \right|}^2 du##

using Parseval’s theorem which states that: ##\int_\infty ^\infty {\left| f(x) \right|}^2 dx=\int_\infty ^\infty {\left| F(u) \right|}^2 du##, we get:

##\int_\infty ^\infty {\left| f_i(x) \right|}^2 dx=4\int_\infty ^\infty {\left| f_f(x) \right|}^2 dx##

The question states that the average noise amplitude is 2 mV in the time domain. Does this mean that:
##\int_\infty ^\infty {\left| f_i(x) \right|}^2 dx=2## ?
 
Last edited:
Physics news on Phys.org
  • #2
Sorry I know this is an old thread, but are you still looking for an answer to this?

MartynaJ said:
The question states that the average noise amplitude is 2 mV in the time domain. Does this mean that:
##\int_\infty ^\infty {\left| f_i(x) \right|}^2 dx=2## ?

I think the 2 mV refers to [itex] |f(x)| [/itex], so the power would be proportional to [itex] |f(x)|^2 [/itex] just like [itex] P = \frac{V^2}{R} [/itex]. I haven't seen the term 'noise amplitude' before to be honest, but it seems like they are asking for the rms value. We can say that the power is proportional to 4 of some arbitrary units (we don't need to worry about them given that the power spectral density is constant).

MartynaJ said:
Relevant Equations:: ##\int_\infty ^\infty {\left| f(x) \right|}^2 dx=\int_\infty ^\infty {\left| F(u) \right|}^2 du##

Before:
##\int_\infty ^\infty {\left| F_i(u) \right|}^2 du=\int_0 ^{40} a^2 du=40 a^2##

I think you can get to the end result sooner. We are told that the noise is uniformly distributed from 0 to 40 MHz (area of a rectangle, as you have found). Therefore, when only considering the noise from 0 to 10 MHz, you can immediately tell that the noise power is now 1/4 of what it previously was (there isn't necessarily a need to write out the integrals with [itex] a^2 [/itex]).

Once we have the power is 1/4 of the previous value, we can find the noise amplitudes. You were basically at the solution. We want to find the value that solves: [tex] x^2 \times 4 = 4 [/tex]

Hope that is of some help.
 

1. What is Parseval’s theorem?

Parseval’s theorem is a mathematical theorem that states the equivalence between the energy in a signal and its Fourier transform. It is used to analyze signals in the frequency domain and is commonly used in fields such as signal processing and electrical engineering.

2. How is Parseval’s theorem applied?

Parseval’s theorem is applied by taking the Fourier transform of a signal, squaring the magnitude of the transformed signal, and then integrating over all frequencies. This integral is equal to the energy of the original signal in the time domain.

3. What are the benefits of using Parseval’s theorem?

Using Parseval’s theorem allows for a more efficient analysis of signals in the frequency domain. It also allows for the calculation of the energy of a signal without having to work directly with the time-domain signal.

4. Are there any limitations to Parseval’s theorem?

One limitation of Parseval’s theorem is that it assumes the signal is periodic. If the signal is not periodic, then the theorem cannot be applied. Additionally, the theorem may not hold for signals that are not square-integrable.

5. Can Parseval’s theorem be applied to any type of signal?

Parseval’s theorem can be applied to any signal that meets the criteria of being periodic and square-integrable. However, it is most commonly used for signals that are continuous and have a finite energy, such as audio signals or electrical signals.

Similar threads

  • Calculus and Beyond Homework Help
Replies
8
Views
669
  • Calculus and Beyond Homework Help
Replies
13
Views
490
  • Calculus and Beyond Homework Help
Replies
1
Views
627
  • Calculus and Beyond Homework Help
Replies
3
Views
589
  • Calculus and Beyond Homework Help
Replies
31
Views
2K
  • Calculus and Beyond Homework Help
Replies
1
Views
351
  • Calculus and Beyond Homework Help
Replies
1
Views
676
  • Calculus and Beyond Homework Help
2
Replies
47
Views
2K
  • Calculus and Beyond Homework Help
Replies
16
Views
1K
  • Calculus and Beyond Homework Help
Replies
17
Views
624
Back
Top