Wavelet programming for audio identification [closed]

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How exactly is a digitally used wavelet?

States Wikipedia

"a wavelet could be created to have a mean C frequency and
short duration of about a 32nd note "

Would it be a data structure containing for example {sampleNumber, frequency}?

If a wavelet is an array of these pairs, how is it applied to the audio data?

How does this wavelet apply to analysis when using an FFT?

What is actually compared to identify the signal?

The answer

I have the impression that you have combined a few different concepts here. The first confused part is the following:

Would it be a data structure containing for example {sampleNumber, frequency}?

It is a continuous function, so choose your preferred way of representing continuous functions in a discrete computer memory, and this could be a wise way to represent it.

The wavelet is applied to the audio signal by convolution (this is actually the next paragraph in the Wikipedia article that you referenced ...), which is relatively standard in most DSP applications (especially audio applications ). Wavelets are really only a particular type of filter in the wider sense of signal processing, in that they have particular properties that are desirable in some applications, but they are still basically filters!

With respect to the comparison performed - it is the presence or absence of a particular frequency in the input signal corresponding to the frequency (or frequencies) that the wavelet is designed to identify.