I just published a guitar tune app myself (Guitar FreaQ)...mostly for fun
and to teach myself android development.

I found that the FFT didn't use that much cpu at all (custom rendering did
though)  The fft algorithm computes N log(N)  calculations.  So if you do a
1024 point fft you are only doing 1024*10 calculations per pass.  If you do
a straight DFT computation per string and compare you will do 1024
calculations per string or 1024*6.  For me, the additional 1024*4
calculations was worth the extra robustness.

On Fri, Nov 19, 2010 at 6:16 PM, Chris Stratton <cs07...@gmail.com> wrote:

> On Oct 26, 11:45 am, Bret Foreman <bret.fore...@gmail.com> wrote:
>
> > As a first cut I would set up two files, record to one while doing an
> > FFT on the other. Alternate the roles of the files every 200mS and
> > display the latest frequency. Do you have experience with FFT
> > windowing to avoid edge harmonics?
>
> If you don't know what string is being played and need to determine
> it, an FFT could make sense.
>
> Since you only have 6 (or 12?) strings to check, you could avoid the
> windowing by calculating a single point of the DFT of a length
> optimized for each string's frequency, normalizing, and comparing them
> to determine which is being played.
>
> Once you do know the string, an FM demodulator algorithm centered at
> the proper frequency might be a superior approach for determining the
> tuning error.
>
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