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Timeline for How to remove aliasing effects?

Current License: CC BY-SA 4.0

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Jul 10, 2022 at 13:34 comment added supercat It's actually not necessary for the sampling rate to be twice the highest frequency that's present in the input, but merely that it be twice the difference between the highest and lowest frequencies that are present in the input. There are many cases where the lowest frequency that's present will be so much lower than the highest that it may as well be zero, but there are others where it may be useful to pass an input through a band-pass filter before sampling.
Jul 10, 2022 at 2:56 comment added user314730 Thanks, James. I am sampling in the time domain at 10 kHz and the likely spurious frequencies I am seeing are at around 3-5 kHz, which is the high end of the frequency domain after I take the FFT out to 5 kHz. As I understand it, you're saying these can't be due to aliasing?
Jul 8, 2022 at 3:00 comment added DKNguyen That is my understanding too except for Nyquist rate which I never use.
Jul 8, 2022 at 2:54 comment added user173271 @DKNguyen ...... so the sample rate is equal to the Nyquist rate when sampling at twice the maximum frequency of interest, and in this case they are both equal to twice the Nyquist frequency.
Jul 8, 2022 at 2:41 comment added user173271 @DKNguyen There is some confusion out there in the usage of the terms "Nyquist Rate", "Nyquist frequency" and "sample rate". My understanding and usage of these terms is to use "sample rate" or "sample frequency" for the sampling frequency, "Nyquist frequency" for half the sample frequency and "Nyquist rate" for twice the bandwidth of the filter limited signal.
Jul 8, 2022 at 2:04 comment added DKNguyen "refer to the "Nyquist frequency" as being the actual sampling frequency itself." Oh god. That happens?
Jul 8, 2022 at 1:49 history edited user173271 CC BY-SA 4.0
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Jul 8, 2022 at 1:31 history answered user173271 CC BY-SA 4.0