I would think the major difficulty of the scenario you outline would be the periodicity of the measurements coinciding with whatever environmental differences impact the device under test during the measurement window. If you get to see the oscillator the *same* 8 hours every day, are those hours in daylight vs night? You might find that you get a particular measured value, and then get a chance to observe it once at some other time and find its behavior is radically different then.
> On Apr 22, 2016, at 6:39 AM, jimlux <[email protected]> wrote: > > All woodpecker kidding aside, this brings up an interesting question. > > For most of the measures we look at: ADEV and related measures, you're > looking at statistics collected essentially continuously (e.g. adjacent > sample frequency) at various time offsets. > > But what about when the observations have gaps? Say you're measuring the > frequency of a spacecraft oscillator, and you can only see it for 8 hours a > day? the description of the frequency variation at a time difference of 24 > hours is useful, even if the integration time for each measurement is, say, > 1000 seconds. > > Maybe such things are so idiosyncratic that the description should be unique > to the situation, or maybe there's no real insight to be gained by a > generalized formulation, as there is with the Leeson model. > > > _______________________________________________ > time-nuts mailing list -- [email protected] > To unsubscribe, go to https://www.febo.com/cgi-bin/mailman/listinfo/time-nuts > and follow the instructions there. _______________________________________________ time-nuts mailing list -- [email protected] To unsubscribe, go to https://www.febo.com/cgi-bin/mailman/listinfo/time-nuts and follow the instructions there.
