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[172]1\hypertarget{classEKFfixed}{
[99]2\section{EKFfixed Class Reference}
3\label{classEKFfixed}\index{EKFfixed@{EKFfixed}}
[172]4}
[99]5{\tt \#include $<$ekf\_\-obj.h$>$}
6
[280]7Inheritance diagram for EKFfixed::\begin{figure}[H]
[99]8\begin{center}
9\leavevmode
[280]10\includegraphics[height=3cm]{classEKFfixed}
[99]11\end{center}
12\end{figure}
[280]13
14
15\subsection{Detailed Description}
16Extended Kalman Filter with full matrices in fixed point arithmetic.
17
18An approximation of the exact Bayesian filter with Gaussian noices and non-linear evolutions of their mean. \subsection*{Public Member Functions}
[99]19\begin{CompactItemize}
20\item 
[172]21\hypertarget{classEKFfixed_cece920bbf58fc72b25a6417b3ef0259}{
22void \textbf{init\_\-ekf} (double Tv)}
23\label{classEKFfixed_cece920bbf58fc72b25a6417b3ef0259}
[99]24
25\item 
[172]26\hypertarget{classEKFfixed_491e636b259dda3b876b7bd492df6b7c}{
27void \textbf{ekf} (double ux, double uy, double isxd, double isyd)}
28\label{classEKFfixed_491e636b259dda3b876b7bd492df6b7c}
[99]29
30\item 
[172]31\hypertarget{classEKFfixed_e77b35e1a11356dbfb1fdfa3017f60d3}{
32void \textbf{prediction} (int $\ast$ux)}
33\label{classEKFfixed_e77b35e1a11356dbfb1fdfa3017f60d3}
[99]34
35\item 
[172]36\hypertarget{classEKFfixed_83ed56b86a056d7dbdd6ce44145fa5f3}{
37void \textbf{correction} (void)}
38\label{classEKFfixed_83ed56b86a056d7dbdd6ce44145fa5f3}
[99]39
40\item 
[172]41\hypertarget{classEKFfixed_dce43355681cfe8f1905db207b4dde8d}{
42void \textbf{update\_\-psi} (void)}
43\label{classEKFfixed_dce43355681cfe8f1905db207b4dde8d}
[99]44
45\item 
[280]46\hypertarget{classEKFfixed_05d1f11bd56305420b56fe83ada6e586}{
47\hyperlink{classEKFfixed_05d1f11bd56305420b56fe83ada6e586}{EKFfixed} ()}
48\label{classEKFfixed_05d1f11bd56305420b56fe83ada6e586}
[99]49
50\begin{CompactList}\small\item\em Default constructor. \item\end{CompactList}\item 
[172]51\hypertarget{classEKFfixed_ddf5334bc1207658fd53698fffbac028}{
52void \hyperlink{classEKFfixed_ddf5334bc1207658fd53698fffbac028}{bayes} (const vec \&dt)}
53\label{classEKFfixed_ddf5334bc1207658fd53698fffbac028}
[99]54
[172]55\begin{CompactList}\small\item\em Here dt = \mbox{[}yt;ut\mbox{]} of appropriate dimensions. \item\end{CompactList}\item 
[280]56\hypertarget{classEKFfixed_f3979e5514fe4278a519ba4481e287ac}{
57\hyperlink{classbdm_1_1epdf}{epdf} \& \hyperlink{classEKFfixed_f3979e5514fe4278a519ba4481e287ac}{posterior} ()}
58\label{classEKFfixed_f3979e5514fe4278a519ba4481e287ac}
[99]59
60\begin{CompactList}\small\item\em dummy! \item\end{CompactList}\item 
[172]61\hypertarget{classEKFfixed_c7fee79e75ad7f0c0e96c5a322cbf44e}{
62void \hyperlink{classEKFfixed_c7fee79e75ad7f0c0e96c5a322cbf44e}{condition} (const vec \&Q0)}
63\label{classEKFfixed_c7fee79e75ad7f0c0e96c5a322cbf44e}
[99]64
65\begin{CompactList}\small\item\em Substitute {\tt val} for {\tt rvc}. \item\end{CompactList}\item 
[280]66\hypertarget{classbdm_1_1BMcond_7506910f93250b44fea505ec4ffb19dc}{
67const RV \& \hyperlink{classbdm_1_1BMcond_7506910f93250b44fea505ec4ffb19dc}{\_\-rvc} () const }
68\label{classbdm_1_1BMcond_7506910f93250b44fea505ec4ffb19dc}
69
70\begin{CompactList}\small\item\em access function \item\end{CompactList}\end{CompactItemize}
71\begin{Indent}{\bf Constructors}\par
72\begin{CompactItemize}
73\item 
74virtual BM $\ast$ \hyperlink{classbdm_1_1BM_c0f027ff91d8459937c6f60ff8e553ff}{\_\-copy\_\-} ()
75\end{CompactItemize}
76\end{Indent}
77\begin{Indent}{\bf Mathematical operations}\par
78\begin{CompactItemize}
79\item 
[255]80\hypertarget{classbdm_1_1BM_1dee3fddaf021e62d925289660a707dc}{
81virtual void \hyperlink{classbdm_1_1BM_1dee3fddaf021e62d925289660a707dc}{bayesB} (const mat \&Dt)}
82\label{classbdm_1_1BM_1dee3fddaf021e62d925289660a707dc}
[99]83
84\begin{CompactList}\small\item\em Batch Bayes rule (columns of Dt are observations). \item\end{CompactList}\item 
[255]85virtual double \hyperlink{classbdm_1_1BM_50257e0c1e5b5c73153ea6e716ad8ae0}{logpred} (const vec \&dt) const
[172]86\item 
[255]87\hypertarget{classbdm_1_1BM_0e8ebe61fb14990abe1254bd3dda5fae}{
88vec \hyperlink{classbdm_1_1BM_0e8ebe61fb14990abe1254bd3dda5fae}{logpred\_\-m} (const mat \&dt) const }
89\label{classbdm_1_1BM_0e8ebe61fb14990abe1254bd3dda5fae}
[180]90
91\begin{CompactList}\small\item\em Matrix version of logpred. \item\end{CompactList}\item 
[280]92\hypertarget{classbdm_1_1BM_688d7a2aced1e06aa1c468d73a9e5eba}{
93virtual epdf $\ast$ \hyperlink{classbdm_1_1BM_688d7a2aced1e06aa1c468d73a9e5eba}{epredictor} () const }
94\label{classbdm_1_1BM_688d7a2aced1e06aa1c468d73a9e5eba}
[180]95
[280]96\begin{CompactList}\small\item\em Constructs a predictive density $ f(d_{t+1} |d_{t}, \ldots d_{0}) $. \item\end{CompactList}\item 
97\hypertarget{classbdm_1_1BM_598b25e3f3d96a5bc00a5faeb5b3c912}{
98virtual mpdf $\ast$ \hyperlink{classbdm_1_1BM_598b25e3f3d96a5bc00a5faeb5b3c912}{predictor} () const }
99\label{classbdm_1_1BM_598b25e3f3d96a5bc00a5faeb5b3c912}
[172]100
[280]101\begin{CompactList}\small\item\em Constructs a conditional density 1-step ahead predictor. \item\end{CompactList}\end{CompactItemize}
102\end{Indent}
103\begin{Indent}{\bf Access to attributes}\par
104\begin{CompactItemize}
105\item 
106\hypertarget{classbdm_1_1BM_ff2d8755ba0b3def927d31305c03b09c}{
107const RV \& \textbf{\_\-drv} () const }
108\label{classbdm_1_1BM_ff2d8755ba0b3def927d31305c03b09c}
109
110\item 
111\hypertarget{classbdm_1_1BM_f135ae6dce7e9f30c9f88229c7930b96}{
112void \textbf{set\_\-drv} (const RV \&rv)}
113\label{classbdm_1_1BM_f135ae6dce7e9f30c9f88229c7930b96}
114
115\item 
116\hypertarget{classbdm_1_1BM_b38d92f17620813ad872d86e01a26e5e}{
117void \textbf{set\_\-rv} (const RV \&rv)}
118\label{classbdm_1_1BM_b38d92f17620813ad872d86e01a26e5e}
119
120\item 
[255]121\hypertarget{classbdm_1_1BM_5be65d37dedfe33a3671e7065f523a70}{
[280]122double \textbf{\_\-ll} () const }
[255]123\label{classbdm_1_1BM_5be65d37dedfe33a3671e7065f523a70}
[99]124
[280]125\item 
[255]126\hypertarget{classbdm_1_1BM_236b3abbcc93594fc97cd86d82c1a83f}{
[280]127void \textbf{set\_\-evalll} (bool evl0)}
[255]128\label{classbdm_1_1BM_236b3abbcc93594fc97cd86d82c1a83f}
[99]129
[172]130\item 
[280]131\hypertarget{classbdm_1_1BM_bb7b0065d6cb722a66b371a8260121e1}{
132virtual const epdf \& \textbf{posterior} () const =0}
133\label{classbdm_1_1BM_bb7b0065d6cb722a66b371a8260121e1}
[172]134
[280]135\item 
136\hypertarget{classbdm_1_1BM_4ed0f8b880e606316ae800f3a011c3a6}{
137virtual const epdf $\ast$ \textbf{\_\-e} () const =0}
138\label{classbdm_1_1BM_4ed0f8b880e606316ae800f3a011c3a6}
139
140\end{CompactItemize}
141\end{Indent}
[99]142\subsection*{Public Attributes}
143\begin{CompactItemize}
144\item 
[172]145\hypertarget{classEKFfixed_d04ddf049475a15e1ba93161aa5586ab}{
146int \textbf{Q} \mbox{[}16\mbox{]}}
147\label{classEKFfixed_d04ddf049475a15e1ba93161aa5586ab}
[99]148
149\item 
[172]150\hypertarget{classEKFfixed_d914213d413b4d8f8d7bb728c5063d5e}{
151int \textbf{R} \mbox{[}4\mbox{]}}
152\label{classEKFfixed_d914213d413b4d8f8d7bb728c5063d5e}
[99]153
154\item 
[172]155\hypertarget{classEKFfixed_7fd20a80b00e9782da676e48eb5b54b3}{
156int \textbf{x\_\-est} \mbox{[}4\mbox{]}}
157\label{classEKFfixed_7fd20a80b00e9782da676e48eb5b54b3}
[99]158
159\item 
[172]160\hypertarget{classEKFfixed_9518fa723d7324f75df7822a589ee196}{
161int \textbf{x\_\-pred} \mbox{[}4\mbox{]}}
162\label{classEKFfixed_9518fa723d7324f75df7822a589ee196}
[99]163
164\item 
[172]165\hypertarget{classEKFfixed_0b731c546a474433c1ea6f36f0125774}{
166int \textbf{P\_\-pred} \mbox{[}16\mbox{]}}
167\label{classEKFfixed_0b731c546a474433c1ea6f36f0125774}
[99]168
169\item 
[172]170\hypertarget{classEKFfixed_b9ec9cb2d092ca3f4ad2a3b4420867ac}{
171int \textbf{P\_\-est} \mbox{[}16\mbox{]}}
172\label{classEKFfixed_b9ec9cb2d092ca3f4ad2a3b4420867ac}
[99]173
174\item 
[172]175\hypertarget{classEKFfixed_5a8040cdb8bb5dca753485dc67db3287}{
176int \textbf{Y\_\-mes} \mbox{[}2\mbox{]}}
177\label{classEKFfixed_5a8040cdb8bb5dca753485dc67db3287}
[99]178
179\item 
[172]180\hypertarget{classEKFfixed_9292e43fb8e6fedfabb3a9b3c2118e33}{
181int \textbf{ukalm} \mbox{[}2\mbox{]}}
182\label{classEKFfixed_9292e43fb8e6fedfabb3a9b3c2118e33}
[99]183
184\item 
[172]185\hypertarget{classEKFfixed_f754902bb769d3b58b89108c76d9a394}{
186int \textbf{Kalm} \mbox{[}8\mbox{]}}
187\label{classEKFfixed_f754902bb769d3b58b89108c76d9a394}
[99]188
189\item 
[172]190\hypertarget{classEKFfixed_bf4b3d55c8d277673bf77f37f6590217}{
191int \textbf{PSI} \mbox{[}16\mbox{]}}
192\label{classEKFfixed_bf4b3d55c8d277673bf77f37f6590217}
[99]193
194\item 
[172]195\hypertarget{classEKFfixed_8a677b253b54696701c1ca0cb6f7a622}{
196int \textbf{temp15a} \mbox{[}16\mbox{]}}
197\label{classEKFfixed_8a677b253b54696701c1ca0cb6f7a622}
[99]198
199\item 
[172]200\hypertarget{classEKFfixed_6d4354dad09286a7a209983732853c5b}{
201int \textbf{cA}}
202\label{classEKFfixed_6d4354dad09286a7a209983732853c5b}
[99]203
204\item 
[172]205\hypertarget{classEKFfixed_eac752adfb921c1c525f8c3b3fd15dad}{
206int \textbf{cB}}
207\label{classEKFfixed_eac752adfb921c1c525f8c3b3fd15dad}
[99]208
209\item 
[172]210\hypertarget{classEKFfixed_2f35ef3dce13131ae9b4427309a1d005}{
211int \textbf{cC}}
212\label{classEKFfixed_2f35ef3dce13131ae9b4427309a1d005}
[99]213
214\item 
[172]215\hypertarget{classEKFfixed_50b31e70bb17cbdde2e28c83b9612c47}{
216int \textbf{cG}}
217\label{classEKFfixed_50b31e70bb17cbdde2e28c83b9612c47}
[99]218
219\item 
[172]220\hypertarget{classEKFfixed_086e18ad28d139b0a2c0f77badc77a9a}{
221int \textbf{cH}}
222\label{classEKFfixed_086e18ad28d139b0a2c0f77badc77a9a}
[99]223
224\item 
[172]225\hypertarget{classEKFfixed_540046e3ab4d0bed4791f397062a626f}{
226long \textbf{temp30a} \mbox{[}4\mbox{]}}
227\label{classEKFfixed_540046e3ab4d0bed4791f397062a626f}
[99]228
229\item 
[172]230\hypertarget{classEKFfixed_ea92b06e2b66c6771828e689bb727b76}{
[255]231\hyperlink{classbdm_1_1enorm}{enorm}$<$ \hyperlink{classfsqmat}{fsqmat} $>$ \textbf{E}}
[172]232\label{classEKFfixed_ea92b06e2b66c6771828e689bb727b76}
[99]233
234\item 
[172]235\hypertarget{classEKFfixed_6e5552506214757d24e59e508f91c8aa}{
236mat \textbf{Ry}}
237\label{classEKFfixed_6e5552506214757d24e59e508f91c8aa}
[99]238
239\end{CompactItemize}
240\subsection*{Protected Attributes}
241\begin{CompactItemize}
242\item 
[280]243\hypertarget{classbdm_1_1BM_c400357e37d27a4834b2b1d9211009ed}{
244RV \hyperlink{classbdm_1_1BM_c400357e37d27a4834b2b1d9211009ed}{drv}}
245\label{classbdm_1_1BM_c400357e37d27a4834b2b1d9211009ed}
[99]246
[280]247\begin{CompactList}\small\item\em Random variable of the data (optional). \item\end{CompactList}\item 
[255]248\hypertarget{classbdm_1_1BM_4064b6559d962633e4372b12f4cd204a}{
249double \hyperlink{classbdm_1_1BM_4064b6559d962633e4372b12f4cd204a}{ll}}
250\label{classbdm_1_1BM_4064b6559d962633e4372b12f4cd204a}
[99]251
252\begin{CompactList}\small\item\em Logarithm of marginalized data likelihood. \item\end{CompactList}\item 
[255]253\hypertarget{classbdm_1_1BM_faff0ad12556fe7dc0e2807d4fd938ee}{
254bool \hyperlink{classbdm_1_1BM_faff0ad12556fe7dc0e2807d4fd938ee}{evalll}}
255\label{classbdm_1_1BM_faff0ad12556fe7dc0e2807d4fd938ee}
[99]256
[172]257\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 computational time. \item\end{CompactList}\item 
[280]258\hypertarget{classbdm_1_1BMcond_1164a90f782a2a323b1ee17242100b39}{
259int \hyperlink{classbdm_1_1BMcond_1164a90f782a2a323b1ee17242100b39}{dimc}}
260\label{classbdm_1_1BMcond_1164a90f782a2a323b1ee17242100b39}
261
262\begin{CompactList}\small\item\em dimension of the conditioning variable \item\end{CompactList}\item 
[255]263\hypertarget{classbdm_1_1BMcond_9a12750776d977408aada06a70093297}{
264RV \hyperlink{classbdm_1_1BMcond_9a12750776d977408aada06a70093297}{rvc}}
265\label{classbdm_1_1BMcond_9a12750776d977408aada06a70093297}
[99]266
267\begin{CompactList}\small\item\em Identificator of the conditioning variable. \item\end{CompactList}\end{CompactItemize}
268
269
[280]270\subsection{Member Function Documentation}
271\hypertarget{classbdm_1_1BM_c0f027ff91d8459937c6f60ff8e553ff}{
272\index{EKFfixed@{EKFfixed}!\_\-copy\_\-@{\_\-copy\_\-}}
273\index{\_\-copy\_\-@{\_\-copy\_\-}!EKFfixed@{EKFfixed}}
274\subsubsection[\_\-copy\_\-]{\setlength{\rightskip}{0pt plus 5cm}virtual BM$\ast$ bdm::BM::\_\-copy\_\- ()\hspace{0.3cm}{\tt  \mbox{[}inline, virtual, inherited\mbox{]}}}}
275\label{classbdm_1_1BM_c0f027ff91d8459937c6f60ff8e553ff}
[99]276
277
[280]278Copy function required in vectors, Arrays of \hyperlink{classbdm_1_1BM}{BM} etc. Have to be DELETED manually! Prototype:
279
280\begin{Code}\begin{verbatim} BM* _copy_(){return new BM(*this);} 
281\end{verbatim}
282\end{Code}
283
284 
285
286Reimplemented in \hyperlink{classbdm_1_1ARX_60c40b5c6abc4c7e464b4ccae64a5a61}{bdm::ARX}.\hypertarget{classbdm_1_1BM_50257e0c1e5b5c73153ea6e716ad8ae0}{
[172]287\index{EKFfixed@{EKFfixed}!logpred@{logpred}}
288\index{logpred@{logpred}!EKFfixed@{EKFfixed}}
[255]289\subsubsection[logpred]{\setlength{\rightskip}{0pt plus 5cm}virtual double bdm::BM::logpred (const vec \& {\em dt}) const\hspace{0.3cm}{\tt  \mbox{[}inline, virtual, inherited\mbox{]}}}}
290\label{classbdm_1_1BM_50257e0c1e5b5c73153ea6e716ad8ae0}
[172]291
292
293Evaluates predictive log-likelihood of the given data record I.e. marginal likelihood of the data with the posterior integrated out.
294
[255]295Reimplemented in \hyperlink{classbdm_1_1ARX_080a7e531e3aa06694112863b15bc6a4}{bdm::ARX}, \hyperlink{classbdm_1_1MixEF_da724da464a75e07521941e430929efa}{bdm::MixEF}, and \hyperlink{classbdm_1_1multiBM_e157b607c1e3fa91d42aeea44458e2bf}{bdm::multiBM}.
[180]296
[280]297Referenced by bdm::BM::logpred\_\-m().
[172]298
[99]299The documentation for this class was generated from the following files:\begin{CompactItemize}
300\item 
[261]301\hyperlink{ekf__obj_8h}{ekf\_\-obj.h}\item 
302ekf\_\-obj.cpp\end{CompactItemize}
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