A solution is provided to the problem of computing a convex set of conditional probability distributions that characterize the state of a nonlinear dynamic system as it evolves in time. The estimator uses the Galerkin approximation to solve Kolmogorov's equation for the diffusion of a continuous-time nonlinear system with discrete- time measurement updates. Fitering of the state is accomplished for a convex set of distributions simultaneously, and closed-form representations of the resulting sets of means and covariances are generated.
Keywords. nonlinear filtering, convex sets of distributions, set-valued estimation
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Electrical and Computer Engineering
|John Kenneyfirstname.lastname@example.org, email@example.com|