The INI has a new website!

This is a legacy webpage. Please visit the new site to ensure you are seeing up to date information.

Skip to content



C4 - Introduction to computational inversion III

Siltanen, S (Helsinki)
Friday 29 July 2011, 09:00-09:45

Seminar Room 1, Newton Institute


Inverse problems arise from indirect measurements of physical quantities. Examples include recovering the internal structure of objects from boundary measurements, for example X-ray attenuation from projection images or electric conductivity distribution from current-to-voltage measurements at the boundary. A defining feature of inverse problems is "ill-posedness", or extreme sensitivity to measurement and modeling errors: two quite different objects may produce almost exactly the same data. This is why specially regularized reconstruction methods are needed for the practical solution of inverse problems. This course explains how to detect ill-posedness in practical measurements and how to design noise-robust computational inversion algorithms. X-ray tomography is used as a guiding example, and Tikhonov regularization is the basic numerical methodology. Matlab software is provided for the participants to enable numerical experiments.

The zip archive contains Matlab files relating to Tomography with explicitly constructed measurement matrix. Feel free to experiment with these files. If you use them as part of your research, please include a reference to the origin and the author of the files.


[pdf ] [pdf ] [zip ]


The video for this talk should appear here if JavaScript is enabled.
If it doesn't, something may have gone wrong with our embedded player.
We'll get it fixed as soon as possible.

Back to top ∧