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Thanks Bill. Also particle and wiener filters (right back to Bayes).
Rocket science. If the predict/update rate is fast enough given the
distance, you are right. I wonder about the performance as the
number of terms increases but that's why we have Moore's Law.
The interesting bit to me is that given multiple
notations (even if all XML), the same similarity
metric should be returned and if persistent, can
be identified by a URI. Not new news.
From: Bill de hOra [mailto:firstname.lastname@example.org]
Bullard, Claude L (Len) wrote:
> Take the vector measures and tie them together with
> URIs across multiple notations for the same observations
> and that is an interesting system for machine learning
> as has been shown time and time again. They aren't
> as useful for targeting munitions;
You might want to look up Kalman Filters.