Hi Jim, On 10/05/2013 05:47 PM, Jim Lux wrote: >> Ah. Then after the initial transient, all you want to do is estimate the >> drift term and remove it from your data. That's not too hard to do with >> a simple least square algorithm. > > yes.. OK. Then we are on the same page. > > I've also made variants of ADEV >> processing that accumulates values such that the linear drift can be >> taken out of the ADEV without re-iterating, but in that case the >> Hadamard does it too. When doing a least square you get frequency and >> drift parameters and can then get a reduced sample-set for ADEV and >> friends to chew on. >> >> You only need to estimate the exponential decay if your samples are >> precious and you need to get those early samples. >> > > Exactly... > > It's a fairly simple model. > > I'll have to look at a bunch of data sets and decide if the > exponential part is something I can just chop off. In the previous > system, the time in the exponential part was a significant fraction of > the total data set, but in this one it seems to be a lot faster. > Cursory estimation by eye makes it look like out of the 2000 samples > in the plot, the transient has died out by 200 samples. Since the > typical data epoch is 10s of thousands of samples, losing the first > 200 is no big deal. > > That's why I was loathe to leap in and turn the full power of Matlab > nonlinear fits into it. Indeed. I'll have some code that probably can do exactly what you want in plain C. Just need a few lines for the prepping of the model to suit the needs.
Toss me a few datasets if you can. Cheers, Magnus _______________________________________________ time-nuts mailing list -- time-nuts@febo.com To unsubscribe, go to https://www.febo.com/cgi-bin/mailman/listinfo/time-nuts and follow the instructions there.
