An efficient stochastic approximation EM algorithm using conditional particle filters
I present a novel method for maximum likelihood parameter estimation in nonlinear/non-Gaussian state-space models. It is an expectation maximization (EM) like method, which uses sequential Monte Carlo (SMC) for the intermediate state inference problem. Contrary to existing SMC-based EM algorithms, h...
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| Format: | Others |
| Language: | English |
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Linköpings universitet, Reglerteknik
2013
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| Online Access: | http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-93459 |