Thanks for the sanity check! :) I was indeed hoping to be able to get away with "not every Nth edge" since that simplifies thing.
On the subject of extracting frequency out of the dataseet, for now I use ordinary least squares. What other approaches do you know of that are used for this particular applicaction? regards, Fred ----- Original Message ----- From: Magnus Danielson <mag...@rubidium.dyndns.org> To: time-nuts@febo.com Cc: Sent: Saturday, May 14, 2011 9:28 AM Subject: Re: [time-nuts] Continuous timestamping reciprocal counter question On 05/13/2011 04:56 PM, Tijd Dingen wrote: > To calculate the frequency from these time stamps you have to do some slop > fitting. If you use a least squares matrix approach for that I could see how > the more random distribution could help prevent singularities. > > The only reason I can see now to really try harder to always get the exact > Nth edge is for numerical solving. As in, should you choose a solver that > only operates optimally for equidistant samples. > > Any thoughts? You don't have to get exactly every Nth edge. But you need to count the edges. A continuous time-stamping counter will count time and edges and the time-stamp will contain both (except in some special conditions where it isn't needed). There are a number of different approaches on how frequency is extracted out of the dataset, however very few of them assumes perfect event count distance. 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. _______________________________________________ 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.
