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SUMMARY:Computing the filter derivative using Sequential Monte Carlo - Ber
 nd Kuhlenschmidt (CCA)
DTSTART:20120314T160000Z
DTEND:20120314T173000Z
UID:TALK36204@talks.cam.ac.uk
CONTACT:Edward Mottram
DESCRIPTION:Sequential Monte Carlo (SMC) methods are widely used computati
 onal tools for Bayesian inference in nonlinear non-Gaussian state space mo
 dels. In this talk\, I present a SMC algorithm for computing the derivativ
 e of the optimal filter in a Hidden Markov Model and study its stability. 
 I will discuss applications to parameter estimation and optimal control.
LOCATION:MR14\, CMS
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