MATH COLLOQUIUM, THURSDAY, FEBRUARY 22, 11:00 AM, STR #138


SPEAKER:     Dr. Yaron Felus, Associate Professor,

Surveying Engineering Department, Ferris State University         


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 White Island of south Victoria Land in west Antarctica will be presented."



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