E-resources
Peer reviewed
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Sarkka, Simo; Hartikainen, Jouni
IEEE transactions on automatic control, 08/2010, Volume: 55, Issue: 8Journal Article
In this note we shall present a new Gaussian approximation based framework for approximate optimal smoothing of non-linear stochastic state space models. The approximation framework can be used for efficiently solving non-linear fixed-interval, fixed-point and fixed-lag optimal smoothing problems. We shall also numerically compare accuracies of approximations, which are based on Taylor series expansion, unscented transformation, central differences and Gauss-Hermite quadrature.
