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Let's build a FIR convolver for Pulseaudio Crossover Rack
Let's build a FIR convolver for Pulseaudio Crossover Rack
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Old 14th October 2019, 10:59 PM   #31
CharlieLaub is offline CharlieLaub  United States
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Quote:
Originally Posted by dc655321 View Post
Sort of?
You, the algorithm designer, must chose what size of blocks your algorithm will work with. The audio application may feed your code blocks of any size though (~4 kilo-frames, for example), so one must be prepared to handle that situation.
Sure, I understand this point 100%. I was just giving an example from what I have experienced under LADSPA. The host gives you some block size. IF you need "more" than you buffer it.

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Originally Posted by dc655321 View Post
No. The output of your algorithm can only be a large as the size of the input block it was given (assuming no output buffering). The rule, y >= b + n - 1, when applied over a segment of input will contain aliased values. Thus the need to overlap and add (or save/discard).

Eg: if your algorithm works in 4 ksample blocks of input, and your FIR filter is 8 ktaps (taps, samples, same thing), clearly you cannot multiply two vectors of unequal length (convolution in frequency domain IS multiplication). So, the 4 ksamples of input are padded with 4 kilo-zeros, yielding an input+zeros length of 8 ksamples. This can then be multiplied with the FIR transform, inverse FFT'd, and B samples of convolved output extracted.
Actually, there is no requirement that the impulse is smaller than the block of data. Where did you get that idea? Remember, outside of the non-zero data I am assuming infinite zeroes. Maybe a theoretical construct, but that is how it is. For example, if you are convolving an impulse with a FIR filter, the impulse is only a couple of samples wide, really. Then what? (that was a rhetorical question).
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Originally Posted by dc655321 View Post
No.
There is always an overlap (hey, it's in the name!) of M-1 points.
It's a stateful algorithm.

With overlap-save, there is no addition, post-convolution, required.



I'm afraid you're missing a few things. But, this is not something that will make sense without a solid understanding of convolution.
I don't see a difference between what you are saying and what I stated in my post. There will be an "overlap". What is that? It means that information produced by a successive convolution also contains information that must be added to adjacent convolutions to yield the "correct" output. This is just a consequence of windowing.
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Old 14th October 2019, 11:23 PM   #32
dc655321 is offline dc655321  United States
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Originally Posted by CharlieLaub View Post
Actually, there is no requirement that the impulse is smaller than the block of data. Where did you get that idea?
Now I have the same question - I don't think I mentioned any such requirement.
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Old 8th November 2019, 02:57 PM   #33
Tfive is offline Tfive  Germany
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@dc655321 any news about your library?
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Old Yesterday, 04:24 PM   #34
dc655321 is offline dc655321  United States
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@dc655321 any news about your library?
@Tfive apologies for the silence (again!).
I just got back late last night from traveling across the country for a two-day job interview. Never had one lasting 2 days before... Brutal.

I will ping you on Gitlab and we can discuss offline exactly what you need in an API (eg: what additions may/may not be required from cvngn for LADSPA use).
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