[ml] Statistics / software question

[Christoph Maier]

Link to the raw data, please.

On Fri, May 11, 2012 at 8:55 PM, Wladyslaw Zbikowski <
embeddedlinuxguy at gmail.com> wrote:

> Hi, my friend Jake has a little project for which we might be able to
> use some statistics expertise.
>
> We are taking analog readings from a device (a voltage pulse). The
> voltage pulse represents the energy of a single X-ray particle (in
> MeV). We know what the energy signature is supposed to look like for
> this particular radioactive material; i.e. there are peaks where
> certain energies are highly represented, and valleys where other
> energy levels are rare. So we would like to correlate our measurement
> with the expected signature.
>
> The problems are:
>
> 1. A lot of noise. We have a signal:noise ratio around 1:1 or as good
> as 4:1, because of background radiation and attempts at shielding.
>
> 2. We don't know exactly how the voltage we read maps to MeV. I.e.
> Voltage is a function of Energy, presumably linear, but we don't know
> exactly the scale (how many MeV per volt).
>
> SO in short, we have a graph of our data, and we want to force-fit it
> to the graph we expect. My idea is to apply noise removal and scaling,
> getting the closest possible match. Any thoughts on this? R? Python?
> Possible topic for a meetup? We can post the graphs and the software
> if anyone is interested to see.
>
> Thanks in advance!
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