Aliased Frequency
Frequency an under-sampled tone masquerades as.
Formula
Variables
Example
f=30 kHz sampled at 44.1 kHz: alias ≈ 14.1 kHz
How it works
When a signal is sampled, the sampler cannot distinguish a tone at frequency f from tones shifted by integer multiples of the sampling rate f_s, because those versions produce the same sequence of sample values. The aliased frequency is the distance from the true frequency to the nearest such multiple, which is why n is chosen as the nearest integer to f / f_s and the absolute value is used. This gives the apparent in-band frequency you would measure after sampling, not the original frequency that was present before sampling.
When to use it
Use this when analyzing sampled data for aliasing, especially in ADC design, audio, vibration, and RF undersampling problems. It is also useful for predicting what frequency a high-frequency tone will appear as after it is sampled below Nyquist.
Worked example, step by step
Suppose a tone at f = 18.7 kHz is sampled at f_s = 8 kHz. Step 1: Compute the ratio f / f_s = 18.7 / 8 = 2.3375. Step 2: Choose the nearest integer multiple: n = 2. Step 3: Compute the aliased frequency: f_a = |f - n f_s| = |18.7 - 2(8)| kHz. Step 4: Simplify: f_a = |18.7 - 16| kHz = 2.7 kHz. Final answer: the 18.7 kHz tone appears after sampling as a 2.7 kHz alias.
Common mistakes to avoid
- Using floor or ceil instead of the nearest integer for n
- Forgetting the absolute value and ending up with a negative frequency
- Confusing the aliased frequency with the original frequency or with the Nyquist frequency
Did You Know?
Aliasing is why wagon wheels appear to spin backwards on film — the frame rate under-samples the motion.
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