MATH COLLOQUIUM, THURSDAY, FEBRUARY 22, , STR #138
SPEAKER: Dr. Yaron Felus, Associate Professor,
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