>Although you might be correct for a frequency of f
>when the sampling frequency is 2f, the theorem correctly stated says
>that it will be good for frquencies UP TO f Hz, i.e. not including f.
as its not an integer measurement then
"up to" and "up to and including" mean the same in real terms
> So while you're correct for one frequency, f, the theorem holds
> 100% true for all frequencies below f and no information is lost.
Ok, let's take it through slowly,
sample a 22kHz signal at 44.1kHz
the result is identical to sampling a 22.05kHz tone
which is amplitude modulated at 500Hz
agree? (if no, then try working it out on paper)
and there are other signals (with FM and AM) which would produce the
so how can we be sure and re-create 22kHz?
We can't, that's a classic case of loss of information.
> The mathematics bear out.
The mathematics is based on an assumption zero information loss in a
where the signal is periodically repeating at a known frequency, and
frequency is picked to be a whole multiple of that periodic frequency.
...but audio is non-periodic and of unknown frequency.
so the maths doesn't bear out your claim.
i.e. information loss increases as you approach the Nyquist frequency.