Aliased Frequency Calculator

Enter sampling rate and input frequency to compute the folded (aliased) frequency, Nyquist limit, and zone.

How to Use

  1. Enter your sampling rate Fs (e.g., 48 kHz).
  2. Enter your input/signal frequency Fin (e.g., 30 kHz).
  3. View the aliased result Falias in the Output section.
  4. Open Show Work to see the folding math and Nyquist zone.

This tool assumes ideal sampling (no anti-alias filter). Real systems often use filtering to prevent aliasing.

Inputs
Provide sampling rate and input frequency. Results update instantly.
Common: 8 kHz, 44.1 kHz, 48 kHz, 96 kHz, 1 MHz
Example: 30 kHz sampled at 48 kHz aliases to 18 kHz
Output
Aliased frequency is the apparent frequency after sampling.
Aliased Frequency (Falias)
—
Nyquist (Fs/2)
—
Nyquist Zone
—
Folded Band
—
Enter Fs and Fin to compute the aliased result.

Markers: Fin (input), Falias (folded), Nyquist.

Show Work (step-by-step)
—
Work is shown in base units (Hz) for clarity and consistency.

Reference

  • Nyquist frequency: Fnyq = Fs / 2
  • Modulo fold: f = Fin mod Fs (wrapped into [0, Fs))
  • Fold to Nyquist band: if f > Fs/2, then Falias = Fs − f, else Falias = f
  • Nyquist zone (1-based): zone = floor(Fin / (Fs/2)) + 1

If Fin is above Fs/2 and there is no anti-alias filter, it will appear as a lower frequency after sampling.

FAQ

What does “aliased frequency” mean?

It’s the frequency you *observe* after sampling, when the original frequency exceeds what the sampling rate can represent without ambiguity.

How do I prevent aliasing?

Use an anti-alias low-pass filter before sampling, or increase the sampling rate so your signal stays below Fs/2.

Why does a higher frequency look like a lower frequency?

Sampling repeats the spectrum every Fs. Frequencies “wrap” and fold around Nyquist.

Tool Info

Last updated:

Updates may include visualization improvements, more unit options, and edge-case handling.