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[19] | 1 | \section{work/mixpp/bdm/estim/libPF.h File Reference} |
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| 2 | \label{libPF_8h}\index{work/mixpp/bdm/estim/libPF.h@{work/mixpp/bdm/estim/libPF.h}} |
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[8] | 3 | Bayesian Filtering using stochastic sampling (Particle Filters). |
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| 4 | |
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| 5 | {\tt \#include $<$itpp/itbase.h$>$}\par |
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[19] | 6 | {\tt \#include \char`\"{}../stat/libBM.h\char`\"{}}\par |
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| 7 | {\tt \#include \char`\"{}../math/libDC.h\char`\"{}}\par |
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| 8 | |
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| 9 | |
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| 10 | Include dependency graph for libPF.h:\nopagebreak |
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| 11 | \begin{figure}[H] |
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| 12 | \begin{center} |
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| 13 | \leavevmode |
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| 14 | \includegraphics[width=135pt]{libPF_8h__incl} |
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| 15 | \end{center} |
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| 16 | \end{figure} |
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[8] | 17 | \subsection*{Classes} |
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| 18 | \begin{CompactItemize} |
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| 19 | \item |
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| 20 | class {\bf PF} |
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| 21 | \begin{CompactList}\small\item\em A Particle Filter prototype. \item\end{CompactList}\item |
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| 22 | class {\bf TrivialPF} |
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| 23 | \begin{CompactList}\small\item\em Trivial particle filter with proposal density that is not conditioned on the data. \item\end{CompactList}\item |
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| 24 | class \textbf{MPF} |
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| 25 | \end{CompactItemize} |
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| 26 | \subsection*{Enumerations} |
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| 27 | \begin{CompactItemize} |
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| 28 | \item |
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| 29 | enum \textbf{RESAMPLING\_\-METHOD} \{ \textbf{MULTINOMIAL} = 0, |
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[19] | 30 | \textbf{STRATIFIED} = 1, |
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[8] | 31 | \textbf{SYSTEMATIC} = 3 |
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| 32 | \} |
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| 33 | \end{CompactItemize} |
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| 34 | |
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| 35 | |
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| 36 | \subsection{Detailed Description} |
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| 37 | Bayesian Filtering using stochastic sampling (Particle Filters). |
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| 38 | |
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| 39 | \begin{Desc} |
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| 40 | \item[Author:]Vaclav Smidl.\end{Desc} |
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| 41 | ----------------------------------- BDM++ - C++ library for Bayesian Decision Making under Uncertainty |
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| 42 | |
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| 43 | Using IT++ for numerical operations ----------------------------------- |
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