Moment quadrature for stochastic filtering

Abstract: Stochastic filtering is an important estimation problem for time series. In this talk, we present a class of filters that represent the filtering distributions by their moments. The key enablement is a quadrature method that uses orthonormal polynomials spanned by the moments. We show that this moment-based filter is asymptotically exact in the order of moments, and that the filter is also computationally efficient and is in line with the state of the art.

numerical analysisoptimization and controldata analysis, statistics and probability

Audience: researchers in the discipline

( paper )

CAM seminar

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