>Creating a 22000 Hz signal from a 250 Hz signal by interpolation, is >*exactly* upsampling
That is not what is shown in that graph. The graph simply shows the continuous-time frequency response of the interpolation polynomials, graphed up to 22kHz. No resampling is depicted, or the frequency responses would show the aliasing associated with that. It's just showing the sinc^2 response of the linear interpolator, and similar for the other polynomials. This is what you'd get if you used those interpolation polynomials to convert a 250Hz sampled signal into a continuous time signal, not a discrete time signal of whatever sampling rate. E On Fri, Aug 21, 2015 at 2:09 AM, Peter S <peter.schoffhau...@gmail.com> wrote: > On 21/08/2015, Ethan Duni <ethan.d...@gmail.com> wrote: > >>In this graph, the signal frequency seems to be 250 Hz, so this graph > >>shows the equivalent of about 22000/250 = 88x oversampling. > > > > That graph just shows the frequency responses of various interpolation > > polynomials. It's not related to oversampling. > > Creating a 22000 Hz signal from a 250 Hz signal by interpolation, is > *exactly* upsampling - the sampling rate changes by a factor of 88x. > It's not bandlimited interpolation (using a windowed sinc > interpolator), hence there is a lot of aliasing above Nyquist. > Irregardless, it's still oversampling - the resulting signal is > sampled with a 88x higher frequency than the original. It's equivalent > to creating a 3,880,800 Hz signal from a 44100 Hz signal. > > -P > _______________________________________________ > music-dsp mailing list > music-dsp@music.columbia.edu > https://lists.columbia.edu/mailman/listinfo/music-dsp >
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