The first bin in the FFT is DC (0 Hz), the second bin is Fs / N
, where Fs
is the sample rate and N
is the size of the FFT. The next bin is 2 * Fs / N
. To express this in general terms, the nth bin is n * Fs / N
.
So if your sample rate, Fs
is say 44.1 kHz and your FFT size, N
is 1024, then the FFT output bins are at:
0: 0 * 44100 / 1024 = 0.0 Hz
1: 1 * 44100 / 1024 = 43.1 Hz
2: 2 * 44100 / 1024 = 86.1 Hz
3: 3 * 44100 / 1024 = 129.2 Hz
4: ...
5: ...
...
511: 511 * 44100 / 1024 = 22006.9 Hz
Note that for a real input signal (imaginary parts all zero) the second half of the FFT (bins from N / 2 + 1
to N - 1
) contain no useful additional information (they have complex conjugate symmetry with the first N / 2 - 1
bins). The last useful bin (for practical aplications) is at N / 2 - 1
, which corresponds to 22006.9 Hz in the above example. The bin at N / 2
represents energy at the Nyquist frequency, i.e. Fs / 2
( = 22050 Hz in this example), but this is in general not of any practical use, since anti-aliasing filters will typically attenuate any signals at and above Fs / 2
.
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