[From Bill Powers (950927.0645 MDT)]
Hans Blom (950927) --
RE: challenge with variable k
You get another WOW for that. But I guess I need some kindergarten
lessons in how your system works (I understand perfectly, of course, but
I have a friend who is pretty dense about complex mathematics...). Could
you walk us through the meanings of the various symbols and expressions?
I realize that I'm asking you to teach Kalman Filter theory (if that's
what it is) from scratch, but I would really appreciate being given a
helping hand here. What I don't grasp is
pxx := pkk * sqr (u) + 2.0 * pdk * u + pdd;
pxk := pkk * u + pdk;
pxd := pdk * u + pdd;
pkk := pkk + pmm;
pdd := pdd + pnn;
and
k := k + (y - x) * pxk / pxx;
d := d + (y - x) * pxd / pxx;
pkk := pkk - sqr (pxk) / pxx;
pdd := pdd - sqr (pxd) / pxx;
pdk := pdk - pxd * pxk / pxx;
{estimate of m and n noise variances}
pmm := pmm + (sqr (k - kold) - pmm) / 20.0; kold := k;
pnn := pnn + (sqr (d - dold) - pnn) / 20.0; dold := d;
... which is pretty much the whole thing.
I'm very impressed with your result.
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Best,
Bill P.