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SUMMARY:Nonlinear filtering algorithms based on averaging over characteris
 tics and on the innovation approach. - Tretyakov\, M (University of Leices
 ter)
DTSTART:20100614T135000Z
DTEND:20100614T144000Z
UID:TALK25293@talks.cam.ac.uk
CONTACT:Mustapha Amrani
DESCRIPTION:It is well known that numerical methods for nonlinear filterin
 g problems\, which directly use the Kallianpur-Striebel formula\, can exhi
 bit computational instabilities due to the presence of very large or very 
 small exponents in both the numerator and denominator of the formula. We o
 btain computationally stable schemes by exploiting the innovation approach
 . We propose Monte Carlo algorithms based on the method of characteristics
  for linear parabolic stochastic partial differential equations. Convergen
 ce and some properties of the considered algorithms are studied. Variance 
 reduction techniques are discussed. Results of some numerical experiments 
 are presented. The talk is based on a joint work with G.N. Milstein.
LOCATION:Seminar Room 1\, Newton Institute
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