On 2015-06-09, Ethan Duni wrote:
The Fourier transform does not exist for functions that blow up to +-
infinity like that. To do frequency domain analysis of those kinds of
signals, you need to use the Laplace and/or Z transforms.
Actually in the distributional setting polynomials do have
On 11-Jun-15 11:00, Sampo Syreeni wrote:
I don't know how useful the resulting Fourier transforms would be to the
original poster, though: their structure is weird to say the least.
Under the Fourier transform polynomials map to linear combinations of
the derivatives of various orders of the
Sampo Syreeni писал 2015-06-11 15:55:
On 2015-06-11, Vadim Zavalishin wrote:
So they can be considered kind of bandlimited, although as I noted
in my other post, it seems to result in DC offsets in their restored
versions, if sinc is windowed.
Not really, if the windowing is done right. The
On 2015-06-11, Theo Verelst wrote:
[...] I don't recommend any of the guys I've read from here to presume
they'll make it high up the mathematical pecking order by assuming all
kinds of previous century generalities, while being even more
imprecise about Hilbert Space related math than
On 2015-06-11, vadim.zavalishin wrote:
Not really, if the windowing is done right. The DC offsets have more
to do with the following integration step.
I'm not sure which integration step you are referring to.
The typical framework starts with BLITs, implemented as interpolated
wavetable
On 6/11/15 1:20 PM, Sampo Syreeni wrote:
On 2015-06-11, Theo Verelst wrote:
[...] I don't recommend any of the guys I've read from here to
presume they'll make it high up the mathematical pecking order by
assuming all kinds of previous century generalities, while being even
more imprecise
When setting up the audio callback for PortAudio you can give it a void* to
some data. Set up the fft plan and set the fft object as the void*.
In the callback you can use a cast to get the fft object from the void*
Good luck
Sent from my iPhone
On 11 Jun 2015, at 16:20, Connor Gettel
HI
While it's cute you all followed my lead to think about simple
continuous signals that are bandwidth limited, such that they can be
used as proper examples for a digitization/synthesis/reconstruction
discipline, I don't recommend any of the guys I've read from here to
presume they'll make
If it is purely for graphic display, the interesting aspect coding-wise
will be timing, so that the display coincides closely enough with the
audio it represents. In this regard, the update rate for a running
display rarely needs to be more than 60 fps, and can often be slower -
so you would
On 10-Jun-15 21:26, Ethan Duni wrote:
With bilateral Laplace transform it's also complicated, because the
damping doesn't work there, except possibly at one specific damping
setting (for an exponent, where for polynomials it doesn't work at
all), yielding a DC
Why isn't that sufficient? Do you
On 6/11/15 5:39 PM, Sampo Syreeni wrote:
On 2015-06-09, robert bristow-johnson wrote:
BTW, i am no longer much enamoured with BLIT and the descendents of
BLIT. eventually it gets to an integrated (or twice or 3 times
integrated) wavetable synthesis, and at that point, i'll just do
Hello Connor,
If you just wanted to do a quick FFT and then using the spectrum to control
synthesis, then I would recommend staying in the callback. If you are doing
overlap-add then set framesPerBuffer to half your window size and combine
the current buffer with the previous buffer to feed into
You may find this article useful:
http://www.rossbencina.com/code/real-time-audio-programming-101-time-waits-for-nothing
It deals with the things to do and not to do when processing audio in
realtime using callbacks.
Athos
On 11 June 2015 at 16:20, Connor Gettel connorget...@me.com wrote:
13 matches
Mail list logo
