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- W343042686 abstract "Conventional forward-backward smoothing (FBS) for Gaussian mixture (GM) problems are based on pruning methods which yield a degenerate hypothesis tree and often lead to underestimated uncertainties. To overcome these shortcomings, we propose an algorithm that is based on merging components in the GM during filtering and smoothing. Compared to FBS based on the N-scan pruning, the proposed algorithm offers better performance in terms of track loss, root mean squared error (RMSE) and normalized estimation error squared (NEES) without increasing the computational complexity." @default.
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- W343042686 date "2014-07-07" @default.
- W343042686 modified "2023-09-26" @default.
- W343042686 title "Merging-based forward-backward smoothing on Gaussian mixtures" @default.
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