By Aalhad Deshmukh | Updated Mar 24, 2022

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Analog audio and video signals cannot be processed directly by digital devices; they must first be converted into binary data via sampling. When the sampling rate is insufficient, the Nyquist–Shannon theorem predicts aliasing—an unwanted distortion where higher‑frequency components masquerade as lower frequencies.

Step 1

Record the sampling rate of your acquisition system. Denote this value as Rs (samples per second).

Step 2

Compute the Nyquist frequency: Ns = Rs / 2. This is the highest frequency that can be accurately represented without aliasing.

Step 3

Identify the signal frequency to be sampled, Fs. Find the nearest integer multiple of Rs that is closest to Fs; denote this integer as Rint. For example, if Rs = 10 Ms/s and Fs = 56 MHz, the closest multiple is 5.

Step 4

Calculate the alias frequency using the formula:
Falias = |(Rs × Rint) – Fs|

This calculation provides the frequency offset introduced by aliasing, enabling engineers to adjust sampling parameters and prevent signal distortion.