RE: Table length reduction

D.C.,

The more I think about this, the more I believe an even better solution is
that the error function be computed for BOTH a linear and cubic spline and
then a given point can only be removed if it simultaneously below a limit
(or within a percentile) for both. This would prevent the cubic spline from
removing elbows and keep linear from removing points in the curve "where
there is about to be a change."

Even with this contraint, it seems like there still be a lot of truly
worthless points removed which is the whole point of the excersise. What do
you think?

Another observation: Since the algorithm computes all the error values as a
first pass and then begins culling starting with the lowest error first, it
seems as though the error values near (2 neighbors) the first removed point
are now invalid (cause they depended on the removed point) and this should
be taken into consideration somehow (either by not allowing the neighbors to
be culled or recomputing the error for the neighbors).

Is it getting hairy enough yet?

Chris Rokusek
Innoveda

> -----Original Message-----
> From: Weston Beal [mailto:weston_beal@mentorg.com]
> Sent: Monday, May 08, 2000 2:02 PM
> To: 'IBIS Mailing list'
> Subject: RE: Table length reduction
>
>
> D.C.,
>
> I think I understand what you're doing, but wouldn't it be easier
> and maybe
> more applicable to do linear interpolation? If the program (simulator or
> translator) that reads the resulting IBIS file does cubic spline then you
> are correct in doing the same in your filter. If the IBIS file is going
> into a program that does piece-wise linear interpolation then the filter
> should do the same, I think.
>
> On a related subject, what do ya'll think about a smoothing filter (least
> square?) to reduce measurement noise in IBIS tables? Is it useful or
> dangerous?
>
> Regards,
> Weston
Received on Mon May 8 15:31:26 2000