Power Spectral Density problem

In summary, the conversation discusses calculating the noise equivalent bandwidth of an amplifier. The suggested approach involves using an integral of the transfer function and the power spectral density function. The conversation also touches on the definition of noise equivalent bandwidth and available learning resources for the topic.
  • #1
FunkyDwarf
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Homework Statement


Calculate the noise equivalent bandwidth of the amplifier.


Homework Equations


A(f) = transfer function of the amplifier
B = (1/S(fo) )* Integral over all values of S(f)



The Attempt at a Solution



Ok we're given the integral of |A(f)| but I am not sure how to go from that to a power spectral density function, because that's what S(f) is isn't it? Initially i used A(f) as S(f), which I am pretty sure is wrong, but it worked in proving the approximation that B = A^2 fc for some charactaristic frequency fc. In this case i simply used S(fo) as A and the intergral as the one given.

I think that assumptions wrong but i don't know how to fix it :(

Thanks
-G
 
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  • #2
I don't know if I'll be able to be of much help on this one. The wikipedia.org page looks to be okay on this subject (as long as nobody edits it...)

http://en.wikipedia.org/wiki/Power_spectral_density

That page also has a pointer to a Wolfram page that you can have pretty good confidence in.

BTW, what is the definition of the Noise Equivalent Bandwidth of an amplifier?

This is an interesting paper from TI... what learning resources do you have for your class?

http://focus.ti.com/lit/an/swra030/swra030.pdf
 
  • #3
Ah hey thanks for replying man, its ok i actually found a past exercise sheet with the same question. Its actually quite hard, i think :(

thanks!
-G
 

1. What is Power Spectral Density (PSD)?

Power Spectral Density is a measure of the power of a signal as a function of frequency. It is often used in signal processing and engineering to analyze the frequency content of a signal.

2. How is PSD calculated?

PSD is calculated by taking the Fourier transform of a signal and squaring its magnitude. This results in a spectrum that shows the power of the signal at different frequencies.

3. What is the difference between PSD and amplitude spectrum?

PSD measures the power of a signal at different frequencies, while amplitude spectrum measures the amplitude or strength of a signal at different frequencies. PSD takes into account both the amplitude and frequency of a signal, while amplitude spectrum only looks at the amplitude.

4. What is the importance of PSD in signal analysis?

PSD is important in signal analysis because it allows us to identify the dominant frequencies in a signal and understand its frequency content. This information can be used to filter out noise and improve the quality of the signal.

5. What are some applications of PSD?

PSD has many applications in various fields such as audio and image processing, vibration analysis, and communication systems. It is also used in scientific research to analyze data from experiments and to study the behavior of complex systems.

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