Answers inline > On Jan 19, 2021, at 16:27, Bob kb8tq <[email protected]> wrote: > > Hi > > Assuming the goal is a normal ADEV or xDEV sort of calculation: > > If you replace the raw phase values with zero that can mess things up > > 0 seconds +20 ns > 1 seconds +22 ns > 2 seconds +23 ns > 3 seconds +25 ns > 4 seconds +27ns > 5 seconds +29 ns > > If you “loose” one of those 20 to 30 ns values and replace it with zero, you > have significantly > changed the data set.
Ok > > Even if you are looking at deltas, Nope. It doesn’t work for deltas. > zero stuffing would be problematic with that > (contrived) phase data set. > > 1 seconds +2 > 2 seconds +1 > 3 seconds +2 > 4 seconds +2 > 5 seconds +2 > > If the objective is something like a PLL then “hold at the last value” is the > only practical > answer to the question. You don’t *have* the next value and you need to stuff > something > into the control loop computation. For a control loop, certainly. For just generating the waveform after DAC using interploation, it works well. So, my suggestion doesn’t cover all use cases, and I learned something. That makes it a good day. DaveD > > Bob > > >> On Jan 19, 2021, at 1:37 PM, Dave Daniel <[email protected]> wrote: >> >> Or one can replace those values with zero. That eliminates them; averaging >> then proceeds without those values altering the most probable correct >> average. >> >> DaveD >> >>> On Jan 19, 2021, at 08:49, Bob kb8tq <[email protected]> wrote: >>> >>> Hi >>> >>> The normal approach to filling a gap is to put in a point that is the >>> average >>> of the two adjacent points. The assumption is that this is a “safe” value >>> that >>> will not blow up the result. That’s probably ok if it is done rarely. The >>> risk is >>> that you are running a filter process (averaging is a low pass filter). >>> >>> If you pull out a *lot* of outliers and replace them, you are doing a lot >>> of filtering. >>> Since you are measuring noise, filtering is very likely to improve the >>> result. >>> The question becomes - how representative is the result after a lot of this >>> or >>> that has been done? >>> >>> Obviously the answer to all this depends on what you are trying to do. If >>> you >>> are running a control loop and the output improves, that’s fine. If you are >>> trying to provide an accurate measure of noise …. maybe not so much :) >>> >>> Bob >>> >>>> On Jan 19, 2021, at 2:15 AM, Gilles Clement <[email protected]> wrote: >>>> >>>> Hi, >>>> Yes outliers removal creates gap in Stable32. >>>> The « fill » function can fills gaps with interpolated values. >>>> It does not change much the graphs, except in the low Tau area (see >>>> attached). >>>> Do you know a discussion of impact of outliers removal ? >>>> Gilles. >>>> >>>> >>>> >>>>> Le 18 janv. 2021 à 22:06, Bob kb8tq <[email protected]> a écrit : >>>>> >>>>> Hi >>>>> >>>>> As you throw away samples that are far off the mean, you reduce the sample >>>>> rate ( or at least create gaps in the record). Dealing with that could be >>>>> difficult. >>>>> >>>>> Bob >>>>> >>>>>>> On Jan 18, 2021, at 1:33 PM, Gilles Clement <[email protected]> wrote: >>>>>>> >>>>>>> Hi >>>>>>> >>>>>>> Very cool !!! >>>>>>> >>>>>>> The red trace is obviously the one to focus on. Some sort of digital >>>>>>> loop that >>>>>>> only operates under the “known good” conditions would seem to make >>>>>>> sense. >>>>>>> >>>>>>> Thanks for sharing >>>>>>> >>>>>>> Bob >>>>>> >>>>>> Hi, >>>>>> I tried something with the idea to consider night records fluctuations >>>>>> as « outliers » as compared to day records. >>>>>> Indeed the 3 days record mean value is flat and the histogram quite >>>>>> gaussian. >>>>>> So I processed the 3 days record (green trace) with Stable32’s « Check >>>>>> Function », >>>>>> while removing outliers with decreasing values of the Sigma Factor. The >>>>>> graph below shows the outcome. >>>>>> The graph with Sigma=0.8 (blue trace) connects rather well with the 1Day >>>>>> record (red trace). >>>>>> Would this be a workable approach ? >>>>>> Best, >>>>>> Gilles. >>>>>> >>>>>> >>>>>> >>>>>> >>>>>> >>>>>> _______________________________________________ >>>>>> time-nuts mailing list -- [email protected] >>>>>> To unsubscribe, go to >>>>>> http://lists.febo.com/mailman/listinfo/time-nuts_lists.febo.com >>>>>> and follow the instructions there. >>>>> >>>>> >>>>> _______________________________________________ >>>>> time-nuts mailing list -- [email protected] >>>>> To unsubscribe, go to >>>>> http://lists.febo.com/mailman/listinfo/time-nuts_lists.febo.com >>>>> and follow the instructions there. >>>> >>>> _______________________________________________ >>>> time-nuts mailing list -- [email protected] >>>> To unsubscribe, go to >>>> http://lists.febo.com/mailman/listinfo/time-nuts_lists.febo.com >>>> and follow the instructions there. >>> >>> >>> _______________________________________________ >>> time-nuts mailing list -- [email protected] >>> To unsubscribe, go to >>> http://lists.febo.com/mailman/listinfo/time-nuts_lists.febo.com >>> and follow the instructions there. >> >> _______________________________________________ >> time-nuts mailing list -- [email protected] >> To unsubscribe, go to >> http://lists.febo.com/mailman/listinfo/time-nuts_lists.febo.com >> and follow the instructions there. > > > _______________________________________________ > time-nuts mailing list -- [email protected] > To unsubscribe, go to > http://lists.febo.com/mailman/listinfo/time-nuts_lists.febo.com > and follow the instructions there. _______________________________________________ time-nuts mailing list -- [email protected] To unsubscribe, go to http://lists.febo.com/mailman/listinfo/time-nuts_lists.febo.com and follow the instructions there.
