12 May
2010
12 May
'10
3 a.m.
On Tue, May 11, 2010 at 4:46 PM, Erik de Castro Lopo
<mle+la(a)mega-nerd.com> wrote:
Fons Adriaensen wrote:
Thanks Erik. I do think this is more appropriate for LAD. I'm not
subscribed there but will get subscribed.
This topic is, for me, mainly about learning something about the topic
of DSP and then applying it to something a bit different. It has
application, I think, to stock market trading, but at the same time
I've run across a few papers here and there talking about 'listening'
to the stock market - converting what's going on into audio to then
viewing the market from another perspective. Our ears are far more
sensitive to changes than our eyes so why not use them? If I develop
something interesting then giving back to the Linux audio community
that has given me so much over the years would be cool. Keeping in
mind that I'm not a programmer I think that is unlikely, but who knows
and why not try?
Addressing your comment about the non-DC bias, I agree so I detrend
all the data first with longer term trend info to remove that
component of the data and give it something approaching zero offset
over time. While not necessarily appropriate for audio, one difference
with stock data is there is no absolute high or low - no real voltage
range - and time is fungible (there aren't necessarily specific time
periods like we have with audio) so I'm looking for things like 30-bar
oscillations, and not necessarily 333 Hz signals. (I hope that's
clear...) Still, I'm free to do anything I want with the data to make
it easier to process which might be completely inappropriate for real
audio data.
Again, thanks for the ideas. Moving this conversation to LAD in the
next day or two but will certainly correspond with this list if
there's interest or anyone off list if they want to.
Cheers,
Mark
2. the sum of the filter outputs equals the
original input.
This is a *hard* problem. Basically none of the classical filter
types have these properties. There are filter sets that can do
this but they are quite esoteric.
Linkwitz-Riley filters:
http://en.wikipedia.org/wiki/Linkwitz-Riley_filter
I'm pretty sure they can just be converted to the digital domain
using the bilinear transform.
I'd have a look at wavelet filters for
example.
Do look at the discrete time version of the continuous wavelet
transform, but from my experience, the discrete dyadic wavelet
transform is a complete waste of time for anything other that
sub-band coding applications.
Also, is this a bit more appropriate for the LAD list?
Erik
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