Here's some sample raw data for those interested in what I'm working
with. Thanks a bunch for all the suggestions.
The overall goal is to take this data, remove the DC bias, linear trend,
and exponential transient baseline; then cleverly excise (or exclude
from processing) areas with obvious artifacts (see Figure 15, IQ pair 4)
for an example of an artifact.
These data plots have had the mean removed, but no detrending done. The
raw data does NOT have the mean removed.
As with many real software development things, the basic algorithms are
simple, it's handling real data with real glitches and anomalies that is
important. So when I collect the data, before I load it into a more
lengthy processing step, I want to do a quick evaluation and see if the
overall data take was bad, or maybe I can process just part of the data
(I'd rather have gaps than bad values).
http://www.luxfamily.com/jimlux/Figure%209.pdf
http://www.luxfamily.com/jimlux/Figure%2011.pdf
http://www.luxfamily.com/jimlux/Figure%2013.pdf
http://www.luxfamily.com/jimlux/Figure%2015.pdf
Raw data for 4 channels
http://www.luxfamily.com/jimlux/data.txt
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