On July 16, 2003 11:50 pm, Zlatin Balevsky wrote:
> Possible improvements over using a fixed number of reference points and
> straight lines between them would be :

Once ng is fully working, this is worth playing with.  We need to optimize it
for good estimations with a minimum of data.  Maybe we can get the 'shape'
of the initial curve from a global estimator and change its co-efficients to
make the node look better and adjust as we route.   Think we want to 
consider more than 10 points.

Ed

> I. Non-linear estimators:  instead of straight lines, user some sort of
> interpolation to create the graph :
> a. If the number of points is fixed around 10, we could use newton
> interpolation or chebyshev polynomials.
> b. For larger number of more dynamic reference points we could use cubic
> or quadric splines - these have the benefit that when one reference
> point moves only its immediate neighbors need to be re-calculated which
> spares us some cpu time while providing even better interpolation than
> the polynomials.
> c. If after some experimental data we notice that the reference points
> tend to form periods, we could even use FFT for the very best of the
> interpolating world ;).
>
> these are only the interpolations that I could remember from a Numerical
> Methods course I took last year; when the textbook finds itself I'll
> probably come up with more information.  Each of the above methods beats
> using straight lines by far though.
>
>
> AND/OR
>
> II  Dynamic number of reference points based on specific events:
> a. adding new reference point for every new sample (yeah right)
> b. adding new reference point only if the estimate turns out to be 9x%
> accurate and removing one if the estimate is less than x% accurate
> c. adding a new ref point if the sample is x distance from the
> specialization of the other reference points (to encourage multiple
> specialization).  and removing one if it they start clustering too much
> d. the opposite of c
>
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