[SciPy-Dev] Overlap-add convolution implementation

[Freddy Rietdijk]

I suppose whether it can be part of `convolve()` depends on whether any
additional options are needed. Unless a working heuristic is found the
block size will have to be a parameter. In case convolution with a variant
signal should be supported the hop size should be considered as well. In my
experience you will want to use an iterative solution though when doing
convolution with a variant signal.

On Sat, Jun 15, 2019 at 7:22 PM <3ukip0s02 at sneakemail.com> wrote:

>
>
> On Sat, Jun 15, 2019 at 12:01 PM Todd wrote:
>
>> I am currently working an an implementation of overlap-add convolution
>> [0].  I have a 1D implementation working and I am going to start expanding
>> it to ND.  Overlap-add convolution can provide significant performance
>> benefits over FFT-based convolution.  Does this make sense for scipy?
>>
>
> Yeah!
>
>
>> First is the name.  We have "convolve" and "fftconvolve" already.  A few
>> options:
>>
>> overall_add_conv
>> oaconvolve
>> oadconvolve
>>
>
> fftconvolve has been folded into convolve and can either be selected
> manually, or will automatically choose direct convolution, whichever is
> likely faster.
>
> Does it make sense for the OLA implementation to also be added as a
> convolve() option, using the "method" parameter?
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