Reduced order model approach for inverse scattering

Liliana Borcea (U of Michigan, Ann Arbor)

Mar 23. 2021, 16:30 — 17:15

I will describe how one can construct a reduced order model from scattering data 
collected by an array of sensors. The construction is based on interpreting the wave propagation as 
a dynamical system that is to be learned from the data. The  states of the dynamical system are the 
snapshots of the wave at discrete time intervals. We only know these at the locations of the sensors 
in the array.  The reduced order model is a Galerkin approximation of the dynamical system that 
can be calculated from such knowledge. I will describe some properties of the reduced order model
and show how it can be used for  solving inverse scattering problems. 

Further Information
Erwin Schrödinger Institute - virtual
Associated Event:
Tomographic Reconstructions and their Startling Applications (Online Workshop)
Wolfgang Drexler (Med U Vienna)
Peter Elbau (U Vienna)
Ronny Ramlau (RICAM, Linz)
Monika Ritsch-Marte (Med Uni Innsbruck)
Otmar Scherzer (U Vienna)
Gerhard Schütz (TU Vienna)