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In this paper we present a nonlinear estimation algorithm that combines generalized polynomial chaos theory and higher moment updates. Polynomial chaos theory is used to predict the evolution of uncertainty of the nonlinear random process, and higher order moment updates are used to estimate the posterior non Gaussian probability density function of the random process. The moments are updated using...
A novel framework for stability analysis of linear and polynomial stochastic systems is presented. The framework is built on generalized polynomial chaos theory, which enables analysis of dynamical systems with probabilistic uncertainty on system parameters with various distributions. The theory allows for the transformation of stochastic problems into a higher dimensional deterministic problem, that...
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