Inverse Problems and Machine Learning

Date: March 29, 2017

Time: 12:00PM - 1:00PM

Location: Bloc 628

Speaker: Isaac Harris, TAMU

Title: A Direct Method for reconstructing inclusions from Electrostatic Data

Abstract: In this talk, we will discuss the use of a Sampling Method to reconstruct impenetrable inclusions from Electrostatic Cauchy data. Sampling Methods allow one to recover unknown obstacles with little to no a prior information. These methods are computationally simple to implement and analytically rigorous. We consider the case of an Impedance (Robin) inclusion where we show that the Dirichlet-to-Neumann mapping can be used to reconstruct such impenetrable sub-regions. We also propose a non-iterative method based on Boundary Integral Equations to reconstruct the impedance parameter from the knowledge of multiple Cauchy pairs. Some numerical reconstructions will be presented in two dimensions. We will also briefly discuss the extension to other Inverse Boundary Value Problems.