Sample Rate

[TheAnalyst via Digitalmars-d]

On Sunday, 10 April 2016 at 14:57:03 UTC, hilop wrote:
> On Saturday, 9 April 2016 at 14:15:38 UTC, Nordlöw wrote:
>> Has anybody more than I thought about representing the sample 
>> rate of a sampled signal collected from sources such as 
>> microphones and digital radio receivers?
>>
>> With it we could automatically relate DFT/FFT bins to real 
>> frequencies and other cool stuff.
>>
>> Maybe we could make it part of the standard solution for 
>> linear algebra processing and units of measurement in D.
>>
>> Destroy.
>
> The magnitude is not hard to represent for a buffer.
> let's say you have a FFT of 512 sample, each bin N represent a 
> sub-sinusoid of a frequency given by (SR/(512*2)) * N. Then 
> you've got the power of this sub-sinusoid with Hypoth(bin.real, 
> bin.imag).
>
> Since amplitude perception is not linear, the Y (A to db, from 
> .0f->.1f to -100f->0.0f scale must be adjusted.
> Since the frequency neither the X scale also (frequency to 
> pitch, from 0->22050 to 0->127). (I don't remember the formula 
> right now but those two converters could be part of the unit 
> framework.)
>
> Now to make the things properly (which means avoiding the 
> artifacts, aka the aliasing or the spectrum folding, due to the 
> cut at the buffer edge), the buffers must be multiplied by a 
> windowing function (e.g hanning, hamming, etc) and overlapped 
> (to maintain the original power spectrum).

Believe me or not but we are living in a world where it's easy to 
get the information, but very few people are able to understand 
the information.
Technician vs Analyst.