MATH
COLLOQUIUM, THURSDAY, FEBRUARY 22,
SPEAKER: Dr. Yaron Felus, Associate
Professor,
Surveying Engineering
Department,
TITLE: The Errors in all
Variables Approach: The Case Study of
Mapping
Geological Lineaments in the South Pole.
Abstract: Least
Squares (LS) adjustment method aims at estimating a vector of parameters x,
from a linear model (y = Ax +e), that includes an
observation vector y, a vector of normally distributed errors e
and a matrix of variables A. However, in this linear model, also known
as the Gauss Markov model, the matrix of variables A is considered as
fixed or error free. This is not the case in many physical systems where errors
exist both in the observations vector y, and in the matrix of variables
A. The Total Least Squares (TLS) method is a relatively new mathematical
concept developed to solve such problems also known as the
Error-In-all-Variable models.
In this presentation a novel
application of the TLS technique will be described to identify spatial pattern
in volcanic cones at West-Antarctica. Different mathematical and computational
methods for pattern recognition and cluster detection will be reviewed and compared
with the TLS method. Tests of the new algorithms on a unique data set collected
using remote sensing and field surveying methods performed in
REFRESHMENTS: 11:00 AM, STR #138
http://www.ferris.edu/htmls/colleges/artsands/Math/MATH_COLLOQUIUM/ColloquiumWeb/index.html