\section{EKFfixed Class Reference} \label{classEKFfixed}\index{EKFfixed@{EKFfixed}} Extended \doxyref{Kalman}{p.}{classKalman} Filter in full matrices. {\tt \#include $<$ekf\_\-obj.h$>$} Inheritance diagram for EKFfixed:\nopagebreak \begin{figure}[H] \begin{center} \leavevmode \includegraphics[width=72pt]{classEKFfixed__inherit__graph} \end{center} \end{figure} Collaboration diagram for EKFfixed:\nopagebreak \begin{figure}[H] \begin{center} \leavevmode \includegraphics[height=400pt]{classEKFfixed__coll__graph} \end{center} \end{figure} \subsection*{Public Member Functions} \begin{CompactItemize} \item void \textbf{init\_\-ekf} (double Tv)\label{classEKFfixed_cece920bbf58fc72b25a6417b3ef0259} \item void \textbf{ekf} (double ux, double uy, double isxd, double isyd)\label{classEKFfixed_491e636b259dda3b876b7bd492df6b7c} \item void \textbf{prediction} (int $\ast$ux)\label{classEKFfixed_e77b35e1a11356dbfb1fdfa3017f60d3} \item void \textbf{correction} (void)\label{classEKFfixed_83ed56b86a056d7dbdd6ce44145fa5f3} \item void \textbf{update\_\-psi} (void)\label{classEKFfixed_dce43355681cfe8f1905db207b4dde8d} \item {\bf EKFfixed} ({\bf RV} rvx, {\bf RV} {\bf rvc})\label{classEKFfixed_64d7b1a39c27b1846bcd5628928748ef} \begin{CompactList}\small\item\em Default constructor. \item\end{CompactList}\item void {\bf bayes} (const vec \&dt)\label{classEKFfixed_ddf5334bc1207658fd53698fffbac028} \begin{CompactList}\small\item\em Here dt = [yt;ut] of appropriate dimensions. \item\end{CompactList}\item {\bf epdf} \& {\bf \_\-epdf} ()\label{classEKFfixed_085cf16c573eda32d8d03619c6c4b518} \begin{CompactList}\small\item\em dummy! \item\end{CompactList}\item void {\bf condition} (const vec \&Q0)\label{classEKFfixed_c7fee79e75ad7f0c0e96c5a322cbf44e} \begin{CompactList}\small\item\em Substitute {\tt val} for {\tt rvc}. \item\end{CompactList}\item void {\bf bayes} (mat Dt)\label{classBM_87b07867fd4c133aa89a18543f68d9f9} \begin{CompactList}\small\item\em Batch Bayes rule (columns of Dt are observations). \item\end{CompactList}\item const {\bf RV} \& {\bf \_\-rv} () const \label{classBM_126bd2595c48e311fc2a7ab72876092a} \begin{CompactList}\small\item\em access function \item\end{CompactList}\item double {\bf \_\-ll} () const \label{classBM_87f4a547d2c29180be88175e5eab9c88} \begin{CompactList}\small\item\em access function \item\end{CompactList}\item const {\bf RV} \& {\bf \_\-rvc} () const \label{classBMcond_3fa60348b2da6b4208bb95b8d146900a} \begin{CompactList}\small\item\em access function \item\end{CompactList}\end{CompactItemize} \subsection*{Public Attributes} \begin{CompactItemize} \item int \textbf{Q} [16]\label{classEKFfixed_d04ddf049475a15e1ba93161aa5586ab} \item int \textbf{R} [4]\label{classEKFfixed_d914213d413b4d8f8d7bb728c5063d5e} \item int \textbf{x\_\-est} [4]\label{classEKFfixed_7fd20a80b00e9782da676e48eb5b54b3} \item int \textbf{x\_\-pred} [4]\label{classEKFfixed_9518fa723d7324f75df7822a589ee196} \item int \textbf{P\_\-pred} [16]\label{classEKFfixed_0b731c546a474433c1ea6f36f0125774} \item int \textbf{P\_\-est} [16]\label{classEKFfixed_b9ec9cb2d092ca3f4ad2a3b4420867ac} \item int \textbf{Y\_\-mes} [2]\label{classEKFfixed_5a8040cdb8bb5dca753485dc67db3287} \item int \textbf{ukalm} [2]\label{classEKFfixed_9292e43fb8e6fedfabb3a9b3c2118e33} \item int \textbf{Kalm} [8]\label{classEKFfixed_f754902bb769d3b58b89108c76d9a394} \item int \textbf{PSI} [16]\label{classEKFfixed_bf4b3d55c8d277673bf77f37f6590217} \item int \textbf{temp15a} [16]\label{classEKFfixed_8a677b253b54696701c1ca0cb6f7a622} \item int \textbf{cA}\label{classEKFfixed_6d4354dad09286a7a209983732853c5b} \item int \textbf{cB}\label{classEKFfixed_eac752adfb921c1c525f8c3b3fd15dad} \item int \textbf{cC}\label{classEKFfixed_2f35ef3dce13131ae9b4427309a1d005} \item int \textbf{cG}\label{classEKFfixed_50b31e70bb17cbdde2e28c83b9612c47} \item int \textbf{cH}\label{classEKFfixed_086e18ad28d139b0a2c0f77badc77a9a} \item long \textbf{temp30a} [4]\label{classEKFfixed_540046e3ab4d0bed4791f397062a626f} \item {\bf enorm}$<$ {\bf fsqmat} $>$ \textbf{E}\label{classEKFfixed_ea92b06e2b66c6771828e689bb727b76} \item mat \textbf{Ry}\label{classEKFfixed_6e5552506214757d24e59e508f91c8aa} \end{CompactItemize} \subsection*{Protected Attributes} \begin{CompactItemize} \item {\bf RV} {\bf rv}\label{classBM_af00f0612fabe66241dd507188cdbf88} \begin{CompactList}\small\item\em Random variable of the posterior. \item\end{CompactList}\item double {\bf ll}\label{classBM_5623fef6572a08c2b53b8c87b82dc979} \begin{CompactList}\small\item\em Logarithm of marginalized data likelihood. \item\end{CompactList}\item bool {\bf evalll}\label{classBM_bf6fb59b30141074f8ee1e2f43d03129} \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 {\bf RV} {\bf rvc}\label{classBMcond_9ba793c8ec453f04d372d17195ed8dec} \begin{CompactList}\small\item\em Identificator of the conditioning variable. \item\end{CompactList}\end{CompactItemize} \subsection{Detailed Description} Extended \doxyref{Kalman}{p.}{classKalman} Filter in full matrices. An approximation of the exact Bayesian filter with Gaussian noices and non-linear evolutions of their mean. The documentation for this class was generated from the following files:\begin{CompactItemize} \item work/mixpp/pmsm/simulator\_\-zdenek/ekf\_\-example/{\bf ekf\_\-obj.h}\item work/mixpp/pmsm/simulator\_\-zdenek/ekf\_\-example/ekf\_\-obj.cpp\end{CompactItemize}