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In article <14484@csli.Stanford.EDU> cphoenix@csli.stanford.edu (Chris Phoenix) writes:
>So I can use suggestions or references on how to improve the hardware, or 
>how to massage noisy data.  Thanks!

Look at your basic signal processing texts as a starting point. (I'm also
a CS type and have little relevant experience).

I have a related question (which I am asking for others in my department),
and that is on the subject of classifying the data returned from a sensor.
We have a project to try and determine the cause of Gamma Ray Observatory
going into "safe hold" mode.  We get the recorded telemetry of some 200
sensors from the tape recorder dump and need to come up with classifications
for the data to then feed into an expert system.  Currently we are using
a neural net to do this classification.  My question is what should we
consider to be noisy data?  The other classifications we have are:
rising, steady, falling, trough, and peak.  What other classifications
should we think about adding?  

Thanks & B Cing U

Buck

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