Deterministic Nonlinear Filtering
نویسندگان
چکیده
A model for nonlinear ltering is considered in which errors in state dynamics and observations are modelled deterministically. Mortensen's deterministic estimator and a minimax estimator are considered. A risk sensitive stochastic lter model with small state and observation noise intensities is also considered. The minimax estimator is obtained in the zero noise intensity limit, using asymptotic properties of a pathwise interpretation of the Zakai stochastic partial diierential equation.
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