\section{work/mixpp/libPF.h File Reference}
\label{libPF_8h}\index{work/mixpp/libPF.h@{work/mixpp/libPF.h}}
Bayesian Filtering using stochastic sampling (Particle Filters). 

{\tt \#include $<$itpp/itbase.h$>$}\par
{\tt \#include \char`\"{}libBM.h\char`\"{}}\par
{\tt \#include \char`\"{}libDC.h\char`\"{}}\par
\subsection*{Classes}
\begin{CompactItemize}
\item 
class {\bf PF}
\begin{CompactList}\small\item\em A Particle Filter prototype. \item\end{CompactList}\item 
class {\bf TrivialPF}
\begin{CompactList}\small\item\em Trivial particle filter with proposal density that is not conditioned on the data. \item\end{CompactList}\item 
class \textbf{MPF}
\end{CompactItemize}
\subsection*{Enumerations}
\begin{CompactItemize}
\item 
enum \textbf{RESAMPLING\_\-METHOD} \{ \textbf{MULTINOMIAL} =  0, 
\textbf{DETERMINISTIC} =  1, 
\textbf{RESIDUAL} =  2, 
\textbf{SYSTEMATIC} =  3
 \}
\end{CompactItemize}


\subsection{Detailed Description}
Bayesian Filtering using stochastic sampling (Particle Filters). 

\begin{Desc}
\item[Author:]Vaclav Smidl.\end{Desc}
----------------------------------- BDM++ - C++ library for Bayesian Decision Making under Uncertainty

Using IT++ for numerical operations -----------------------------------