Tuesday,
December 6, 2005, 12:15 p.m. GWC 409
Dept. Math. & Stats.
Using State-of-the-Art NLP Solvers in System Identification and Beyond
Abstract
Our work is lately predominantly in optimization and it
has two substantial components, one of a service nature
and one in interdisciplinary research. We will give an
overview of the first and report in some detail about
an ongoing research project in system identification.
On the service side there are two major aspects of our
work. We provide the two webpages which rank first in a
Google search for "optimization software". The first is a
guide to mostly "free-for-research" sofware, the second a
collection of comparisons of such software. The other
service we provide is one third of all interactive
solvers for optimization problems accessible through the
NEOS gateway (neos.mcs.anl.gov).
Starting with a CLAS interdiscplinary fellowship we
established an interdiscplinary research program in the
area of system identification as it is needed in chemical,
electrical, and other engineering discplines. We will
give an overview of the mathematical problems faced in
this work and how we solved them computationally. This
then naturally links to our knowledge about state-of-the-art
optimization algorithms which are essential in this and,
in turn, the problems we solve provide challenging tests
for these algorithms.
For further information please contact:
mittelmann@asu.edu