Published: April 14, 2016
Event Description:
Christian Lucero, Department of Statistics, Indiana University

The Role of Optimal Experimental Design In the Solution of Inverse Problems

Inverse problems persist in nearly every scientific field. Many inverse problems of
interest are ill-posed and require the use of regularization to obtain stable estimates of
the model parameters. One way to aid in the solution of inverse problems is to carefully
design experiments in order to reduce the ill-conditioning of the system matrix while
simultaneously collecting the best quality data. The focus of this talk is to briefly
introduce inverse problems to the uninitiated and to give an overview of how to use
A -optimal design criteria to obtain optimal experimental designs in both the
well-posed and ill-posed cases.

 
Contact Information:
Name: Ian Cunningham
Phone: 303-492-4668
Email: amassist@colorado.edu