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[Help-gsl] Sparse Levenberg-Marquardt
From: |
Tom Banwell |
Subject: |
[Help-gsl] Sparse Levenberg-Marquardt |
Date: |
Tue, 15 Sep 2009 09:54:41 +0000 |
Hi Everyone,
I was wondering if you could help me. I have a nonlinear least squares problem
that has a large number of parameters, greater than 1,000. I am currently
solving it using the current version of GSL, Levenberg-Marquardt algorithm.
This works well but it is slow and takes several seconds. I would ideally like
it to be a lot less time, and have read that I can exploit the spareness of the
jacobians using QR factorization. Most of my parameters are not dependent on
other parameters and my jacobian is therefore quite sparse.
I was wondering if anyone knows the answers to my follwing questions:
1) How to exploit the sparseness of Jacobians in Levenberg-Marquardt using QR.
2) How to exploit the sparseness of Jacobians in Levenberg-Marquardt
alternative ways.
3) If it is possible to do this in the current GSL.
4) If not currently possible, will the sparseness be exploited in GSL at a
later date.
5) Other algorithms or libraries I could use.
Thanks,
Tom
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