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SUMMARY:C4 - Introduction to computational inversion IV - Siltanen\, S (He
 lsinki)
DTSTART:20110729T100000Z
DTEND:20110729T104500Z
UID:TALK32176@talks.cam.ac.uk
CONTACT:Mustapha Amrani
DESCRIPTION: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 meas
 urements at the boundary. A defining feature of inverse problems is "ill-p
 osedness"\, 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 pract
 ical solution of inverse problems. This course explains how to detect ill-
 posedness in practical measurements and how to design noise-robust computa
 tional 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.
 \n
LOCATION:Seminar Room 1\, Newton Institute
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