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
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