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SUMMARY:Implicit particle methods for high dimensional highly nonlinear sy
 stems - Miller\, R (Oregon State University)
DTSTART:20140317T121500Z
DTEND:20140317T125500Z
UID:TALK51458@talks.cam.ac.uk
CONTACT:Mustapha Amrani
DESCRIPTION:The implicit particle filter is one of a number of recently-pr
 oposed particle filtering schemes in which the trajectory of each particle
  is informed by observations within each assimilation cycle. In the case o
 f observations defined by a linear function of the state vector\, taken ev
 ery time step of the numerical model\, the implicit particle filter is equ
 ivalent to the optimal importance filter\, i.e.\, at each step\, any given
  particle is drawn from the density of the system conditioned jointly upon
  the observation and the state of the particle at the previous time. The o
 ptimal importance filter was implemented for a shallow water model with O(
 10^4) state variables\, and performed well with nominal demands on computi
 ng resources\, but it exhibited some characteristics of the degeneracy som
 e authors have predicted. We note the similarity of our scheme to other re
 cently-devised schemes\, and propose a potential solution in the form of a
  fixed-lag smoother.\n
LOCATION:Seminar Room 1\, Newton Institute
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