Then it has compute out of that peak, so we can even just print

the locations of the peaks, so iploc is the peaks or

the peaks that it has found within the array of the FFT.

It's better to show it in Hertz so we print IP

frequency, is the frequency of the peaks it has found, right?

Then this has gone to the F0 detection,

so it has identified the fundamental frequency.

And the fundamental frequency has been chosen to be 443 Hertz,

which makes sense, we're analyzing a novo sound, an A4.

And then out of this fundamental frequency it has chosen

the peaks that are harmonics of these, so each frequency is

the set of harmonics that it has identified in this particular location.

So it has identified all these harmonics,

the other peaks have not been considered harmonics.

Of course, we have chosen a threshold, and

a given set of parameters that has limited the number

of harmonics to these 6,000, so it becomes easier,

so we just have analyze up into this harmonic.

Okay, then we generate these harmonics as a spectrum and

so it has generated yh, so we plot the absolute value of yh.

We're going to see the magnitude

of the complete spectrum, but

let's plot it just in DB so we will just

plot(20*log10(abs(Yh.

And let's just take only, let's say the first 70 samples,

so from the beginning to the sample 70.

So we focus on the first harmonics,

which are the ones that basically we have generated, okay.

So these are the harmonics that

we basically we have the synthesized spectrum.

On top of that we can plot the signal that

from the original sound that we have recomputed so x2, the x2 spectrum.

Okay, so we plot on top of that the absolute value of x2,