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ISIPTA
1999
IEEE

Nonlinear Filtering of Convex Sets of Probability Distributions

9 years 18 days ago
Nonlinear Filtering of Convex Sets of Probability Distributions
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 di usion of a continuous-time nonlinear system with discrete-time measurement updates. Filtering 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 ltering theory, convex sets of probability distributions, set-valued estimation
John Kenney, Wynn C. Stirling
Added 04 Aug 2010
Updated 04 Aug 2010
Type Conference
Year 1999
Where ISIPTA
Authors John Kenney, Wynn C. Stirling
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