Gradient-free maximum likelihood parameter estimation with particle filters
In this paper we address the problem of on-line estimation of unknown static parameters in non-linear non-Gaussian state-space models. We consider a particle filtering method and employ two gradient-free Stochastic Approximation (SA) methods to maximize recursively the likelihood function, the Finit...
| Main Authors: | , , , |
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| Format: | Conference item |
| Published: |
2006
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