Approximation errors and model reduction with an application in optical diffusion tomography

@inproceedings{Arridge2006ApproximationEA,
  title={Approximation errors and model reduction with an application in optical diffusion tomography},
  author={Simon R. Arridge and Jari P. Kaipio and Ville Kolehmainen and Martin Schweiger and Erkki Somersalo and Tanja Tarvainen and Marko Vauhkonen},
  year={2006}
}
Model reduction is often required in several applications, typically due to limited available time, computer memory or other restrictions. In problems that are related to partial differential equations, this often means that we are bound to use sparse meshes in the model for the forward problem. Conversely, if we are given more and more accurate measurements, we have to employ increasingly accurate forward problem solvers in order to exploit the information in the measurements. Optical… CONTINUE READING
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