Signal Power Distribution Upon Resampling

In summary, when a 25 Hz signal is sampled at 100 Hz without anti-aliasing filters, the DFT results in a series of spikes at 25 Hz, 75 Hz, 125 Hz, 175 Hz, etc. When the same signal enters a 60 Hz system, the DFT results in repeating spikes in sets of three. The original 25 Hz signal will appear as 25 Hz, while the first alias at 75 Hz will appear as 15 Hz and the second alias at 125 Hz will appear as 5 Hz to the 60 Hz system. According to Parseval's theorem, the power of the signal at 25 Hz from the 100 Hz system will be equal to the combined
  • #1
dwlink
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Suppose we have a real 25 Hz signal that is sampled at 100 Hz without any anti-aliasing filters.

Taking the DFT results in a series of spikes 25 Hz, 75 Hz, 125 Hz, 175 Hz etc.

Now suppose the 25 Hz signal after it enters the 100 Hz system now enters a 60 Hz system. If we take the DFT now, we see the same repeating spikes as before, however now they are in sets of three.

For a 60 Hz system, the original 25 Hz signal will look like 25 Hz, but the 75 Hz (first alias) will appear as a 15Hz signal to the 60 Hz system. The 2nd alias at 125 Hz will appear as a 5 Hz signal to the 60 Hz system.

Now if we look at the signal power in the 25 Hz signal from the system that samples at 100 Hz and add up the power of the 5 Hz, 15 Hz, and 25 Hz spikes from the 60 Hz system - we will see they are equal according to Parseval's theorem.

But, how exactly do I figure out a closed form way of expressing what fraction of the power goes to each of the individual frequencies?

I tried to fit the signal sin(2*pi*25*n/100) to
a1*sin(2*pi*5*n/60) + a2*sin(2*pi*15*n/60) + a3*sin(2*pi*25*n/60) but had no luck when trying to fit the signals (yes I know the power and amplitude coefficients will be different).

Am I doing the Fourier transform wrong? Can anyone point me to a reference that discusses this topic? Thanks
 
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  • #2
dwlink said:
Now suppose the 25 Hz signal after it enters the 100 Hz system now enters a 60 Hz system.
Sorry, we can't answer your question because we don't know what that sentence means. Please clarify.
 

FAQ: Signal Power Distribution Upon Resampling

1. What is signal power distribution upon resampling?

Signal power distribution upon resampling refers to the process of redistributing the power of a signal when it is resampled, or converted to a different sampling rate. This can be important for maintaining the integrity and accuracy of the signal in digital signal processing applications.

2. Why is signal power distribution important in resampling?

Signal power distribution is important in resampling because it helps to maintain the accuracy and quality of the resampled signal. If the power is not appropriately redistributed, it can lead to errors and distortion in the signal.

3. How is signal power distribution calculated during resampling?

There are various methods for calculating signal power distribution during resampling, including linear interpolation, sinc interpolation, and polyphase filtering. These methods use mathematical algorithms to redistribute the signal power to maintain its integrity.

4. What factors can affect signal power distribution during resampling?

The sampling rate, filter type, and filter cutoff frequency can all affect signal power distribution during resampling. Additionally, the type of signal being resampled and the desired outcome can also impact the distribution of power.

5. How does signal power distribution impact the accuracy of the resampled signal?

Proper signal power distribution is crucial for maintaining the accuracy of the resampled signal. If the power is not appropriately redistributed, it can lead to errors and distortion in the signal, resulting in a loss of accuracy. This is especially important in high precision applications, such as in scientific research or medical diagnostics.

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