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FrankE
2018-09-17 19:40:30 +02:00
parent ed46dd65dd
commit 1f44af390d
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tex/chapters/estimation.tex
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@@ -26,7 +26,7 @@ In the case of particle filters the MMSE estimate equals to the weighted-average
\hat{\mStateVec}_t := \frac{1}{W_t} \sum_{i=1}^{N} w^i_t \mStateVec^i_t \, \text{,} \hat{\mStateVec}_t := \frac{1}{W_t} \sum_{i=1}^{N} w^i_t \mStateVec^i_t \, \text{,}
\end{equation} \end{equation}
\commentByMarkus{Passt die Notation so?} \commentByMarkus{Passt die Notation so?}
\commentByFrank{sieht fuer mich auf den ersten blick nach korrektem weighted average aller partikel aus} \commentByFrank{sieht fuer mich auf den ersten blick nach korrektem weighted average aller partikel aus. was stoert dich?}
where $W_t=\sum_{i=1}^{N}w^i_t$ is the sum of all weights. where $W_t=\sum_{i=1}^{N}w^i_t$ is the sum of all weights.
While producing an overall good result in many situations, it fails when the posterior is multimodal. While producing an overall good result in many situations, it fails when the posterior is multimodal.
In these situations the weighted-average estimate will find the estimate somewhere between the modes. In these situations the weighted-average estimate will find the estimate somewhere between the modes.