IMI Interdisciplinary Mathematics InstituteCollege of Arts and Sciences

Numerical Algorithms for Nonlinear Filtering Problems

  • Nov. 21, 2014
  • 1 p.m.
  • LeConte 312

Abstract

We consider a nonlinear filtering problem where a signal process is modeled by a stochastic differential equation and the observation is perturbed by a white noise. The goal of nonlinear filtering is to find the best estimation of the signal process based on the observation. Some well known approaches include Kalman filter, Particle filter and Zakai filter. In this talk, we shall present several novel numerical algorithms to solve nonlinear filtering problems efficiently. Both theoretical results and numerical experiments will be presented.

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