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SUMMARY:Adaptive and stochastic algorithms for piecewise constant EIT and 
 DC resistivity problems with many measurements - Asher\, U (University of 
 British Columbia)
DTSTART:20110823T104500Z
DTEND:20110823T113000Z
UID:TALK32457@talks.cam.ac.uk
CONTACT:Mustapha Amrani
DESCRIPTION:We develop fast numerical methods for the practical solution o
 f the famous EIT and DC-resistivity problems in the presence of discontinu
 ities and potentially many experiments or data. \n\nBased on a Gauss-Newto
 n (GN) approach coupled with preconditioned conjugate gradient (PCG) itera
 tions\, we propose two algorithms. One determines adaptively the number of
  inner PCG iterations required to stably and effectively carry out each GN
  iteration. The other algorithm\, useful especially in the presence of man
 y experiments\, employs a randomly chosen subset of experiments at each GN
  iteration that is controlled using a cross validation approach. Numerical
  examples demonstrate the efficacy of our algorithms.\n\n\n
LOCATION:Seminar Room 1\, Newton Institute
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