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08/18/08 14:28:04 (16 years ago)
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smidl
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  • doc/latex/classEKFful__unQR.tex

    r99 r140  
    1 \section{EKFfull Class Reference} 
    2 \label{classEKFfull}\index{EKFfull@{EKFfull}} 
    3 Extended \doxyref{Kalman}{p.}{classKalman} Filter in full matrices.   
     1\section{EKFful\_\-unQR Class Reference} 
     2\label{classEKFful__unQR}\index{EKFful\_\-unQR@{EKFful\_\-unQR}} 
     3Extended \doxyref{Kalman}{p.}{classKalman} filter with unknown {\tt Q} and {\tt R}.   
    44 
    55 
    6 {\tt \#include $<$libKF.h$>$} 
     6{\tt \#include $<$ekf\_\-templ.h$>$} 
    77 
    8 Inheritance diagram for EKFfull:\nopagebreak 
     8Inheritance diagram for EKFful\_\-unQR:\nopagebreak 
    99\begin{figure}[H] 
    1010\begin{center} 
    1111\leavevmode 
    12 \includegraphics[width=78pt]{classEKFfull__inherit__graph} 
     12\includegraphics[width=102pt]{classEKFful__unQR__inherit__graph} 
    1313\end{center} 
    1414\end{figure} 
    15 Collaboration diagram for EKFfull:\nopagebreak 
     15Collaboration diagram for EKFful\_\-unQR:\nopagebreak 
    1616\begin{figure}[H] 
    1717\begin{center} 
    1818\leavevmode 
    19 \includegraphics[height=400pt]{classEKFfull__coll__graph} 
     19\includegraphics[height=400pt]{classEKFful__unQR__coll__graph} 
    2020\end{center} 
    2121\end{figure} 
    … …  
    2323\begin{CompactItemize} 
    2424\item  
    25 {\bf EKFfull} ({\bf RV} rvx, {\bf RV} rvy, {\bf RV} rvu)\label{classEKFfull_67ac4de96fd025197da767fe0472c7f7} 
     25{\bf EKFful\_\-unQR} ({\bf RV} rx, {\bf RV} ry, {\bf RV} ru, {\bf RV} rQR)\label{classEKFful__unQR_873e3a72264f6e777c4443220db15d79} 
    2626 
    2727\begin{CompactList}\small\item\em Default constructor. \item\end{CompactList}\item  
     28void {\bf condition} (const vec \&QR0)\label{classEKFful__unQR_b586e534c8a8d219561b0c020329d412} 
     29 
     30\begin{CompactList}\small\item\em Substitute {\tt val} for {\tt rvc}. \item\end{CompactList}\item  
    2831void {\bf set\_\-parameters} ({\bf diffbifn} $\ast$pfxu, {\bf diffbifn} $\ast$phxu, const mat Q0, const mat R0)\label{classEKFfull_fc753106e0d4cf68e4f2160fd54458c0} 
    2932 
    … …  
    3235 
    3336\begin{CompactList}\small\item\em Here dt = [yt;ut] of appropriate dimensions. \item\end{CompactList}\item  
     37void {\bf bayes} (mat Dt)\label{classBM_87b07867fd4c133aa89a18543f68d9f9} 
     38 
     39\begin{CompactList}\small\item\em Batch Bayes rule (columns of Dt are observations). \item\end{CompactList}\item  
    3440void {\bf set\_\-est} (vec mu0, mat P0)\label{classEKFfull_7bb76ea74c144ea0b36db99f94750b7b} 
    3541 
    … …  
    3844 
    3945\begin{CompactList}\small\item\em dummy! \item\end{CompactList}\item  
    40 void {\bf bayes} (mat Dt)\label{classBM_87b07867fd4c133aa89a18543f68d9f9} 
    41  
    42 \begin{CompactList}\small\item\em Batch Bayes rule (columns of Dt are observations). \item\end{CompactList}\item  
    4346const {\bf RV} \& {\bf \_\-rv} () const \label{classBM_126bd2595c48e311fc2a7ab72876092a} 
    4447 
    4548\begin{CompactList}\small\item\em access function \item\end{CompactList}\item  
    4649double {\bf \_\-ll} () const \label{classBM_87f4a547d2c29180be88175e5eab9c88} 
     50 
     51\begin{CompactList}\small\item\em access function \item\end{CompactList}\item  
     52const {\bf RV} \& {\bf \_\-rvc} () const \label{classBMcond_3fa60348b2da6b4208bb95b8d146900a} 
    4753 
    4854\begin{CompactList}\small\item\em access function \item\end{CompactList}\end{CompactItemize} 
    … …  
    104110 
    105111\item  
     112bool {\bf evalll}\label{classBM_bf6fb59b30141074f8ee1e2f43d03129} 
     113 
     114\begin{CompactList}\small\item\em If true, the filter will compute likelihood of the data record and store it in {\tt ll} . Set to false if you want to save time. \item\end{CompactList}\item  
     115double {\bf ll}\label{classBM_5623fef6572a08c2b53b8c87b82dc979} 
     116 
     117\begin{CompactList}\small\item\em Logarithm of marginalized data likelihood. \item\end{CompactList}\item  
    106118{\bf RV} {\bf rv}\label{classBM_af00f0612fabe66241dd507188cdbf88} 
    107119 
    108120\begin{CompactList}\small\item\em Random variable of the posterior. \item\end{CompactList}\item  
    109 double {\bf ll}\label{classBM_5623fef6572a08c2b53b8c87b82dc979} 
     121{\bf RV} {\bf rvc}\label{classBMcond_9ba793c8ec453f04d372d17195ed8dec} 
    110122 
    111 \begin{CompactList}\small\item\em Logarithm of marginalized data likelihood. \item\end{CompactList}\item  
    112 bool {\bf evalll}\label{classBM_bf6fb59b30141074f8ee1e2f43d03129} 
    113  
    114 \begin{CompactList}\small\item\em If true, the filter will compute likelihood of the data record and store it in {\tt ll} . Set to false if you want to save time. \item\end{CompactList}\end{CompactItemize} 
     123\begin{CompactList}\small\item\em Identificator of the conditioning variable. \item\end{CompactList}\end{CompactItemize} 
    115124\subsection*{Friends} 
    116125\begin{CompactItemize} 
    … …  
    122131 
    123132\subsection{Detailed Description} 
    124 Extended \doxyref{Kalman}{p.}{classKalman} Filter in full matrices.  
     133Extended \doxyref{Kalman}{p.}{classKalman} filter with unknown {\tt Q} and {\tt R}.  
    125134 
    126 An approximation of the exact Bayesian filter with Gaussian noices and non-linear evolutions of their mean.  
    127  
    128 The documentation for this class was generated from the following files:\begin{CompactItemize} 
     135The documentation for this class was generated from the following file:\begin{CompactItemize} 
    129136\item  
    130 work/mixpp/bdm/estim/{\bf libKF.h}\item  
    131 work/mixpp/bdm/estim/libKF.cpp\end{CompactItemize} 
     137work/mixpp/bdm/estim/{\bf ekf\_\-templ.h}\end{CompactItemize}