Maximum frequency, not bandwidth?

AI Thread Summary
The discussion highlights a common misconception regarding the Nyquist frequency, emphasizing that the maximum frequency of a signal, rather than its bandwidth, dictates the required sampling rate for accurate reconstruction. It argues that the term "bandwidth" is misleading in this context. A signal with a spectral content from 40-50MHz sampled at 20MHz demonstrates no aliasing, illustrating this point. To reconstruct the original signal without additional information, sampling must occur at twice the maximum frequency. However, if the center frequency is known, sampling at twice the bandwidth suffices.
freddyfish
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Hey

In many places on the Internet you can read how the Nyquist frequency must be at least as high as the signals bandwidth in order to properly reconstruct the signal. Isn't this a big misnomer, since it is not the bandwidth, but the highest frequency of the signal that determines the necessary sampling rate? Why would then the word "bandwidth" still be used in this context? :smile:
 
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Try to make a drawing in the frequency domain of a signal with a spectral content from 40-50MHz that you sample at 20MHz. You should see there is no aliasing.
If you want to reconstruct the original signal you will of course need extra information about the centre frequency of the original signal.

So if you want to reconstruct the original signal without extra available information, you need to sample at 2x the maximum frequency. If you have some extra information, such as the centre frequency, 2x the bandwidth will do.
 
Thanks for your answer :biggrin:
 
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