root/doc/latex/classEKFfixed.tex @ 100

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1\section{EKFfixed Class Reference}
2\label{classEKFfixed}\index{EKFfixed@{EKFfixed}}
3Extended \doxyref{Kalman}{p.}{classKalman} Filter in full matrices. 
4
5
6{\tt \#include $<$ekf\_\-obj.h$>$}
7
8Inheritance diagram for EKFfixed:\nopagebreak
9\begin{figure}[H]
10\begin{center}
11\leavevmode
12\includegraphics[width=72pt]{classEKFfixed__inherit__graph}
13\end{center}
14\end{figure}
15Collaboration diagram for EKFfixed:\nopagebreak
16\begin{figure}[H]
17\begin{center}
18\leavevmode
19\includegraphics[height=400pt]{classEKFfixed__coll__graph}
20\end{center}
21\end{figure}
22\subsection*{Public Member Functions}
23\begin{CompactItemize}
24\item 
25void \textbf{init\_\-ekf} (double Tv)\label{classEKFfixed_cece920bbf58fc72b25a6417b3ef0259}
26
27\item 
28void \textbf{ekf} (double ux, double uy, double isxd, double isyd)\label{classEKFfixed_491e636b259dda3b876b7bd492df6b7c}
29
30\item 
31void \textbf{prediction} (int $\ast$ux)\label{classEKFfixed_e77b35e1a11356dbfb1fdfa3017f60d3}
32
33\item 
34void \textbf{correction} (void)\label{classEKFfixed_83ed56b86a056d7dbdd6ce44145fa5f3}
35
36\item 
37void \textbf{update\_\-psi} (void)\label{classEKFfixed_dce43355681cfe8f1905db207b4dde8d}
38
39\item 
40{\bf EKFfixed} ({\bf RV} rvx, {\bf RV} {\bf rvc})\label{classEKFfixed_64d7b1a39c27b1846bcd5628928748ef}
41
42\begin{CompactList}\small\item\em Default constructor. \item\end{CompactList}\item 
43void {\bf bayes} (const vec \&dt)\label{classEKFfixed_ddf5334bc1207658fd53698fffbac028}
44
45\begin{CompactList}\small\item\em Here dt = [yt;ut] of appropriate dimensions. \item\end{CompactList}\item 
46{\bf epdf} \& {\bf \_\-epdf} ()\label{classEKFfixed_085cf16c573eda32d8d03619c6c4b518}
47
48\begin{CompactList}\small\item\em dummy! \item\end{CompactList}\item 
49void {\bf condition} (const vec \&Q0)\label{classEKFfixed_c7fee79e75ad7f0c0e96c5a322cbf44e}
50
51\begin{CompactList}\small\item\em Substitute {\tt val} for {\tt rvc}. \item\end{CompactList}\item 
52void {\bf bayes} (mat Dt)\label{classBM_87b07867fd4c133aa89a18543f68d9f9}
53
54\begin{CompactList}\small\item\em Batch Bayes rule (columns of Dt are observations). \item\end{CompactList}\item 
55const {\bf RV} \& {\bf \_\-rv} () const \label{classBM_126bd2595c48e311fc2a7ab72876092a}
56
57\begin{CompactList}\small\item\em access function \item\end{CompactList}\item 
58double {\bf \_\-ll} () const \label{classBM_87f4a547d2c29180be88175e5eab9c88}
59
60\begin{CompactList}\small\item\em access function \item\end{CompactList}\item 
61const {\bf RV} \& {\bf \_\-rvc} () const \label{classBMcond_3fa60348b2da6b4208bb95b8d146900a}
62
63\begin{CompactList}\small\item\em access function \item\end{CompactList}\end{CompactItemize}
64\subsection*{Public Attributes}
65\begin{CompactItemize}
66\item 
67int \textbf{Q} [16]\label{classEKFfixed_d04ddf049475a15e1ba93161aa5586ab}
68
69\item 
70int \textbf{R} [4]\label{classEKFfixed_d914213d413b4d8f8d7bb728c5063d5e}
71
72\item 
73int \textbf{x\_\-est} [4]\label{classEKFfixed_7fd20a80b00e9782da676e48eb5b54b3}
74
75\item 
76int \textbf{x\_\-pred} [4]\label{classEKFfixed_9518fa723d7324f75df7822a589ee196}
77
78\item 
79int \textbf{P\_\-pred} [16]\label{classEKFfixed_0b731c546a474433c1ea6f36f0125774}
80
81\item 
82int \textbf{P\_\-est} [16]\label{classEKFfixed_b9ec9cb2d092ca3f4ad2a3b4420867ac}
83
84\item 
85int \textbf{Y\_\-mes} [2]\label{classEKFfixed_5a8040cdb8bb5dca753485dc67db3287}
86
87\item 
88int \textbf{ukalm} [2]\label{classEKFfixed_9292e43fb8e6fedfabb3a9b3c2118e33}
89
90\item 
91int \textbf{Kalm} [8]\label{classEKFfixed_f754902bb769d3b58b89108c76d9a394}
92
93\item 
94int \textbf{PSI} [16]\label{classEKFfixed_bf4b3d55c8d277673bf77f37f6590217}
95
96\item 
97int \textbf{temp15a} [16]\label{classEKFfixed_8a677b253b54696701c1ca0cb6f7a622}
98
99\item 
100int \textbf{cA}\label{classEKFfixed_6d4354dad09286a7a209983732853c5b}
101
102\item 
103int \textbf{cB}\label{classEKFfixed_eac752adfb921c1c525f8c3b3fd15dad}
104
105\item 
106int \textbf{cC}\label{classEKFfixed_2f35ef3dce13131ae9b4427309a1d005}
107
108\item 
109int \textbf{cG}\label{classEKFfixed_50b31e70bb17cbdde2e28c83b9612c47}
110
111\item 
112int \textbf{cH}\label{classEKFfixed_086e18ad28d139b0a2c0f77badc77a9a}
113
114\item 
115long \textbf{temp30a} [4]\label{classEKFfixed_540046e3ab4d0bed4791f397062a626f}
116
117\item 
118{\bf enorm}$<$ {\bf fsqmat} $>$ \textbf{E}\label{classEKFfixed_ea92b06e2b66c6771828e689bb727b76}
119
120\item 
121mat \textbf{Ry}\label{classEKFfixed_6e5552506214757d24e59e508f91c8aa}
122
123\end{CompactItemize}
124\subsection*{Protected Attributes}
125\begin{CompactItemize}
126\item 
127{\bf RV} {\bf rv}\label{classBM_af00f0612fabe66241dd507188cdbf88}
128
129\begin{CompactList}\small\item\em Random variable of the posterior. \item\end{CompactList}\item 
130double {\bf ll}\label{classBM_5623fef6572a08c2b53b8c87b82dc979}
131
132\begin{CompactList}\small\item\em Logarithm of marginalized data likelihood. \item\end{CompactList}\item 
133bool {\bf evalll}\label{classBM_bf6fb59b30141074f8ee1e2f43d03129}
134
135\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 
136{\bf RV} {\bf rvc}\label{classBMcond_9ba793c8ec453f04d372d17195ed8dec}
137
138\begin{CompactList}\small\item\em Identificator of the conditioning variable. \item\end{CompactList}\end{CompactItemize}
139
140
141\subsection{Detailed Description}
142Extended \doxyref{Kalman}{p.}{classKalman} Filter in full matrices.
143
144An approximation of the exact Bayesian filter with Gaussian noices and non-linear evolutions of their mean.
145
146The documentation for this class was generated from the following files:\begin{CompactItemize}
147\item 
148work/mixpp/pmsm/simulator\_\-zdenek/ekf\_\-example/{\bf ekf\_\-obj.h}\item 
149work/mixpp/pmsm/simulator\_\-zdenek/ekf\_\-example/ekf\_\-obj.cpp\end{CompactItemize}
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