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Nonlinear least square problem

Hallo, sorry for multiposting, but I am really looking
for some hint to solve my problem. And no, I don't
use Matlab, but maybe the matlab people have an idea
nevertheless.

I have to solve a nonlinear least square problem.
Let me tell you some background first. Imagine
you have a tool to process some work piece, say
polishing some piece of glas. The tool behaves
different on different locations of the piece,
and I can describe that behaviour. Now the tool
shall smooth the surface of the workpiece.
Next I have information about the piece before
handling it. What I have to find is optimal
time curve for the tool to obtain a perfectly
smooth surface.

How to formulate the problem?
Given a time vector (t_j) I have a function
g which calculates the remaining error (e_i)
(e_i) = g(t_j)
The rest error is given at, say, 100 points,
(t_j) is searched at 200 points.
My idea was to make the (t_j) a function of
some few parameters (t_j) = h(p_k), say 15
parameters. So the concatenated function
(e_i) = g(t_j) = g(h(p_k)) =: f(p_k) is to be minimized.
in the sense (e_i)-c -Min, where c is a constant,
the end level of the surface.

To solve this problem I use a "C" implementation
of the Levenberg-Marquardt algorithm as you can find
it in the LevMar Package (www.ics.forth.gr/~lourakis/levmar/).

The function g contains the information about the
tool and about the initial surface. For the function
h I tried several approaches, making the time a
cubic spline of a selected times, or making it some
polynmial or...

Now what is my problem? With the above I do find
solutions, however a lot of solutions seem to
give very similar remaining errors. The only problem
is that the corresponding time vectors, which are
(t_j_optimal) = h(p_k_optimal) look very different
from optimal solution to optimal solution.
In particular the optimization algorithm often prefers
solutions where the time vector is heavily oscillating.

Now this is something I _must_ suppress, but I have no
idea how. The oscillation of the (t_j) depend of
the ansatz of h, of the number of parameters (p_k).
If f would be a linear function, then the matrix
representing it would be a band matrix with a lot
of diagonals nonzero. How many depends on the
ratio tool diameter to piece diameter.

Now what are my question: Is the problem properly
formulated? Can I expect to find non-oscillating
solutions? Is it normal that taking more parameters
(p_k) makes the thing worse? What else should I
consider? Is this more verbal description sufficient?

Thank you very much in advance.


Apr 3 '08 #1
1 2113
In article
<03**********************************@r9g2000prd.g ooglegroups.com>,
Uwe Kotyczka <uw**********@web.dewrote:
Hallo, sorry for multiposting, but I am really looking
for some hint to solve my problem. And no, I don't
use Matlab, but maybe the matlab people have an idea
nevertheless.
No apology required, since you seem to have
cross-posted appropriately, and not multi-posted.
Multi-posting is posting the same message one
at a time to more than one group. I see in
the Newsgroups: header line that you posted
to several groups at once. Furthermore the
number of groups is not out of bounds, and
the groups are appropriate to the question
and, presumably, your interests.

Unfortunately, I cannot help with the actual question. :)

--
Michael Press
Apr 5 '08 #2

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