In the late 1960s, Hewlett-Packard engineers worked up a program to have the 5360A "Computing Pig" (so-called from its weight, 55 pounds without plug-ins) compute a "fractional frequency standard deviation." It appears to be similar to the Allen Deviation; I've never figured out the difference and would appreciate hearing from someone with stronger math skills who can explain the two.
Jeremy On Mon, Jan 9, 2017 at 2:00 PM Bob kb8tq <kb...@n1k.org> wrote: > Hi > > > > > On Jan 9, 2017, at 4:49 PM, Magnus Danielson <mag...@rubidium.dyndns.org> > wrote: > > > > > > Scott, > > > > > > On 01/09/2017 07:41 PM, Scott Stobbe wrote: > > >> I could be wrong here, but it is my understanding that Allan's > pioneering > > >> work was in response to finding a statistic which is convergent to 1/f > > >> noise. Ordinary standard deviation is not convergent to 1/f processes. > So I > > >> don't know that trying to compare the two is wise. Disclaimer: I could > be > > >> totally wrong, if someone has better grasp on how the allan deviation > came > > >> to be, please correct me. > > > > > > There where precursor work to Allans Feb 1966 article, but essentially > that where he amalgamed several properties into one to rule them all > (almost). It is indeed the non-convergent properties which motivates a > stronger method. > > > > > > A number of outfits were measuring and spec’ing short term stability in > the 1950’s and early 1960’s. Some were doing measures that are pretty close > to ADEV. Others were doing straight standard deviation of frequency > measurements. Since both got tossed up as “short term stability” confusion > was the main result. NIST came in (as it rightly should) and gave us a > measurement that does converge. They also spend the next two decades > > thumping on a bunch of hard heads to get everybody to use the measurement > rather than something with more issues. Once that effort was underway, we > got a whole raft of alternatives that each have benefits in certain areas. > > ADEV is far from the only measure that could be properly be used today to > characterize short term stability. > > > > Bob > > > > > Standard statistics is relevant for many of the basic blocks, bit things > work differently with the non-convergent noise. > > > Another aspect which was important then was the fact that it was a > counter-based measure. Some of the assumptions is due to the fact that they > used counters. I asked David some questions about why the integral looks > the way it does, and well, it reflects the hardware at the time. > > > > > > What drives Allan vs. standard deviation is that extra derive function > before squaring > > > The bias functions that Allan derives for M-sample is really the > behavior of the s-deviation. See Allan variance wikipedia article as there > is good references there for the bias function. That bias function is > really illustrating the lack of convergence for M-sample standard > deviation. The Allan is really a power-average over the 2-sample standard > deviation. > > > > > > Cheers, > > > Magnus > > > > > >> On Wed, Jan 4, 2017 at 3:12 PM, Attila Kinali <att...@kinali.ch> wrote: > > > > _______________________________________________ > > 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. > > -- Sent from Gmail Mobile _______________________________________________ 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.