Philosophy rant: Frequency is a model. You can use tools that build on that model to describe your signal in terms of frequency, but none of them are going to be perfect. A pure 10hz tone is a mathematical abstraction which you'll not find in any digital signal or measurable phenomenon. But, *ooh boy!* is that abstraction useful for modeling real things.
If you have an extremely clean signal and you want an extremely accurate measurement, my recommendation is to forgo fourier transforms (which introduce noise and resolution limits) and use optimization or measurement techniques in the time domain. In your example, *zero crossings are the easiest and best solution* as Steffan suggests. Another interesting approach, which I mention for scholarly purposes, would be to design a digital filter with a sloping magnitude response (even the simplest one-pole lowpass could do) and apply it across the signal. You can measure the change in the signal's power (toward the end, because the sudden beginning of a sine wave produces noise) and find the frequency for which the filter's transfer function produces that attenuation. This filter-based technique (and related ones) can generalize to other problems where zero-crossings are less useful. – Evan Balster creator of imitone <http://imitone.com> On Thu, Jan 26, 2017 at 9:20 AM, STEFFAN DIEDRICHSEN <sdiedrich...@me.com> wrote: > At that length, you can count zero-crossings. But that’s not a valid > answer, I’d assume. > But I found a nice paper on determining frequencies with FFTs using a > gaussian window. Pretty accurate results. > > Best, > > Steffan > > > On 26.01.2017|KW4, at 15:24, Theo Verelst <theo...@theover.org> wrote: > > Say the sample length is long enough for any purpose, like 10 seconds. > > > > _______________________________________________ > dupswapdrop: music-dsp mailing list > music-dsp@music.columbia.edu > https://lists.columbia.edu/mailman/listinfo/music-dsp >
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