Note Special Day and Time
Abstract:
Inverse problems are problems where one is looking for causes for an
observed or a desired effect. Examples include computerized tomography
(i.e., the inversion of a Radon transform), inverse scattering,
and parameter identification in (partial) differential equations.
Inverse problems lead to models that are ill-posed in the sense that small
errors in the data can lead to arbitrarily large errors in the results.
Therefore, on needs special types of algorithms called "regularization
methods". We outline the functional analytic theory of such methods
(especially iterative ones) and present numerical examples.
This seminar is easily accessible to persons with disabilities. For more information or for assistance, please contact the Mathematics Department at 743-3500.