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1\hypertarget{classEKFCh__du__kQ}{
2\section{EKFCh\_\-du\_\-kQ Class Reference}
3\label{classEKFCh__du__kQ}\index{EKFCh\_\-du\_\-kQ@{EKFCh\_\-du\_\-kQ}}
4}
5Extended Kalman filter with unknown {\tt Q} and delta u. 
6
7
8Inheritance diagram for EKFCh\_\-du\_\-kQ:\nopagebreak
9\begin{figure}[H]
10\begin{center}
11\leavevmode
12\includegraphics[width=124pt]{classEKFCh__du__kQ__inherit__graph}
13\end{center}
14\end{figure}
15Collaboration diagram for EKFCh\_\-du\_\-kQ:\nopagebreak
16\begin{figure}[H]
17\begin{center}
18\leavevmode
19\includegraphics[width=400pt]{classEKFCh__du__kQ__coll__graph}
20\end{center}
21\end{figure}
22\subsection*{Public Member Functions}
23\begin{CompactItemize}
24\item 
25\hypertarget{classEKFCh__du__kQ_a12fe15d132a88587b91103b8615436f}{
26\hyperlink{classEKFCh__du__kQ_a12fe15d132a88587b91103b8615436f}{EKFCh\_\-du\_\-kQ} (\hyperlink{classbdm_1_1RV}{RV} rx, \hyperlink{classbdm_1_1RV}{RV} ry, \hyperlink{classbdm_1_1RV}{RV} ru, \hyperlink{classbdm_1_1RV}{RV} rC)}
27\label{classEKFCh__du__kQ_a12fe15d132a88587b91103b8615436f}
28
29\begin{CompactList}\small\item\em Default constructor. \item\end{CompactList}\item 
30\hypertarget{classEKFCh__du__kQ_5ca289a257ae9d2a1c4ba112234d2e0c}{
31void \textbf{set\_\-ref} (const \hyperlink{classchmat}{chmat} \&Qref0)}
32\label{classEKFCh__du__kQ_5ca289a257ae9d2a1c4ba112234d2e0c}
33
34\item 
35\hypertarget{classEKFCh__du__kQ_2e6654c66d5cd436619361579ddb6543}{
36void \hyperlink{classEKFCh__du__kQ_2e6654c66d5cd436619361579ddb6543}{condition} (const vec \&val)}
37\label{classEKFCh__du__kQ_2e6654c66d5cd436619361579ddb6543}
38
39\begin{CompactList}\small\item\em Substitute {\tt val} for {\tt rvc}. \item\end{CompactList}\item 
40\hypertarget{classbdm_1_1EKFCh_50f9fbffad721f35e5ccb75d0f6b842a}{
41void \hyperlink{classbdm_1_1EKFCh_50f9fbffad721f35e5ccb75d0f6b842a}{set\_\-parameters} (diffbifn $\ast$\hyperlink{classbdm_1_1EKFCh_e1e895f994398a55bc425551fc275ba3}{pfxu}, diffbifn $\ast$\hyperlink{classbdm_1_1EKFCh_6b34c69641826322467b704e8252f317}{phxu}, const \hyperlink{classchmat}{chmat} Q0, const \hyperlink{classchmat}{chmat} R0)}
42\label{classbdm_1_1EKFCh_50f9fbffad721f35e5ccb75d0f6b842a}
43
44\begin{CompactList}\small\item\em Set nonlinear functions for mean values and covariance matrices. \item\end{CompactList}\item 
45\hypertarget{classbdm_1_1KalmanCh_ab3a87ba1831e53f193a9dfbaf56a879}{
46void \hyperlink{classbdm_1_1KalmanCh_ab3a87ba1831e53f193a9dfbaf56a879}{set\_\-parameters} (const mat \&A0, const mat \&B0, const mat \&C0, const mat \&D0, const \hyperlink{classchmat}{chmat} \&R0, const \hyperlink{classchmat}{chmat} \&Q0)}
47\label{classbdm_1_1KalmanCh_ab3a87ba1831e53f193a9dfbaf56a879}
48
49\begin{CompactList}\small\item\em Set parameters with check of relevance. \item\end{CompactList}\item 
50\hypertarget{classbdm_1_1EKFCh_4c8609c37290b158f88a31dae4047225}{
51void \hyperlink{classbdm_1_1EKFCh_4c8609c37290b158f88a31dae4047225}{bayes} (const vec \&dt)}
52\label{classbdm_1_1EKFCh_4c8609c37290b158f88a31dae4047225}
53
54\begin{CompactList}\small\item\em Here dt = \mbox{[}yt;ut\mbox{]} of appropriate dimensions. \item\end{CompactList}\item 
55\hypertarget{classbdm_1_1KalmanCh_f559387dd38bd6002be490cc62987290}{
56void \hyperlink{classbdm_1_1KalmanCh_f559387dd38bd6002be490cc62987290}{set\_\-est} (const vec \&mu0, const \hyperlink{classchmat}{chmat} \&P0)}
57\label{classbdm_1_1KalmanCh_f559387dd38bd6002be490cc62987290}
58
59\begin{CompactList}\small\item\em Set estimate values, used e.g. in initialization. \item\end{CompactList}\item 
60\hypertarget{classbdm_1_1Kalman_93b5936ba397f13c05f52885c545f42d}{
61const epdf \& \hyperlink{classbdm_1_1Kalman_93b5936ba397f13c05f52885c545f42d}{\_\-epdf} () const }
62\label{classbdm_1_1Kalman_93b5936ba397f13c05f52885c545f42d}
63
64\begin{CompactList}\small\item\em access function \item\end{CompactList}\item 
65\hypertarget{classbdm_1_1Kalman_c34989b1e53c7d4ecdaea63a95ddbd77}{
66const enorm$<$ \hyperlink{classchmat}{chmat} $>$ $\ast$ \hyperlink{classbdm_1_1Kalman_c34989b1e53c7d4ecdaea63a95ddbd77}{\_\-e} () const }
67\label{classbdm_1_1Kalman_c34989b1e53c7d4ecdaea63a95ddbd77}
68
69\begin{CompactList}\small\item\em Returns a pointer to the epdf representing posterior density on parameters. Use with care! \item\end{CompactList}\item 
70\hypertarget{classbdm_1_1Kalman_c788ec6e6c6f5f5861ae8a56d8ede277}{
71mat \& \hyperlink{classbdm_1_1Kalman_c788ec6e6c6f5f5861ae8a56d8ede277}{\_\-\_\-K} ()}
72\label{classbdm_1_1Kalman_c788ec6e6c6f5f5861ae8a56d8ede277}
73
74\begin{CompactList}\small\item\em access function \item\end{CompactList}\item 
75\hypertarget{classbdm_1_1Kalman_a250d1dbe7bba861dba2a324520cfa48}{
76vec \hyperlink{classbdm_1_1Kalman_a250d1dbe7bba861dba2a324520cfa48}{\_\-dP} ()}
77\label{classbdm_1_1Kalman_a250d1dbe7bba861dba2a324520cfa48}
78
79\begin{CompactList}\small\item\em access function \item\end{CompactList}\item 
80\hypertarget{classbdm_1_1BM_1dee3fddaf021e62d925289660a707dc}{
81virtual void \hyperlink{classbdm_1_1BM_1dee3fddaf021e62d925289660a707dc}{bayesB} (const mat \&Dt)}
82\label{classbdm_1_1BM_1dee3fddaf021e62d925289660a707dc}
83
84\begin{CompactList}\small\item\em Batch Bayes rule (columns of Dt are observations). \item\end{CompactList}\item 
85virtual double \hyperlink{classbdm_1_1BM_50257e0c1e5b5c73153ea6e716ad8ae0}{logpred} (const vec \&dt) const
86\item 
87\hypertarget{classbdm_1_1BM_0e8ebe61fb14990abe1254bd3dda5fae}{
88vec \hyperlink{classbdm_1_1BM_0e8ebe61fb14990abe1254bd3dda5fae}{logpred\_\-m} (const mat \&dt) const }
89\label{classbdm_1_1BM_0e8ebe61fb14990abe1254bd3dda5fae}
90
91\begin{CompactList}\small\item\em Matrix version of logpred. \item\end{CompactList}\item 
92\hypertarget{classbdm_1_1BM_710e7d69c0d8791fb41a7cd4683cca2c}{
93virtual epdf $\ast$ \hyperlink{classbdm_1_1BM_710e7d69c0d8791fb41a7cd4683cca2c}{predictor} (const RV \&\hyperlink{classbdm_1_1BM_18d6db4af8ee42077741d9e3618153ca}{rv}) const }
94\label{classbdm_1_1BM_710e7d69c0d8791fb41a7cd4683cca2c}
95
96\begin{CompactList}\small\item\em Constructs a predictive density (marginal density on data). \item\end{CompactList}\item 
97\hypertarget{classbdm_1_1BM_40a3c891996391e3135518053a917793}{
98const RV \& \hyperlink{classbdm_1_1BM_40a3c891996391e3135518053a917793}{\_\-rv} () const }
99\label{classbdm_1_1BM_40a3c891996391e3135518053a917793}
100
101\begin{CompactList}\small\item\em access function \item\end{CompactList}\item 
102\hypertarget{classbdm_1_1BM_5be65d37dedfe33a3671e7065f523a70}{
103double \hyperlink{classbdm_1_1BM_5be65d37dedfe33a3671e7065f523a70}{\_\-ll} () const }
104\label{classbdm_1_1BM_5be65d37dedfe33a3671e7065f523a70}
105
106\begin{CompactList}\small\item\em access function \item\end{CompactList}\item 
107\hypertarget{classbdm_1_1BM_236b3abbcc93594fc97cd86d82c1a83f}{
108void \hyperlink{classbdm_1_1BM_236b3abbcc93594fc97cd86d82c1a83f}{set\_\-evalll} (bool evl0)}
109\label{classbdm_1_1BM_236b3abbcc93594fc97cd86d82c1a83f}
110
111\begin{CompactList}\small\item\em access function \item\end{CompactList}\item 
112virtual BM $\ast$ \hyperlink{classbdm_1_1BM_3efb3098172f1f67564a312fe732473e}{\_\-copy\_\-} (bool changerv=false)
113\item 
114\hypertarget{classbdm_1_1BMcond_7506910f93250b44fea505ec4ffb19dc}{
115const RV \& \hyperlink{classbdm_1_1BMcond_7506910f93250b44fea505ec4ffb19dc}{\_\-rvc} () const }
116\label{classbdm_1_1BMcond_7506910f93250b44fea505ec4ffb19dc}
117
118\begin{CompactList}\small\item\em access function \item\end{CompactList}\end{CompactItemize}
119\subsection*{Protected Attributes}
120\begin{CompactItemize}
121\item 
122\hypertarget{classbdm_1_1EKFCh_e1e895f994398a55bc425551fc275ba3}{
123diffbifn $\ast$ \hyperlink{classbdm_1_1EKFCh_e1e895f994398a55bc425551fc275ba3}{pfxu}}
124\label{classbdm_1_1EKFCh_e1e895f994398a55bc425551fc275ba3}
125
126\begin{CompactList}\small\item\em Internal Model f(x,u). \item\end{CompactList}\item 
127\hypertarget{classbdm_1_1EKFCh_6b34c69641826322467b704e8252f317}{
128diffbifn $\ast$ \hyperlink{classbdm_1_1EKFCh_6b34c69641826322467b704e8252f317}{phxu}}
129\label{classbdm_1_1EKFCh_6b34c69641826322467b704e8252f317}
130
131\begin{CompactList}\small\item\em Observation Model h(x,u). \item\end{CompactList}\item 
132\hypertarget{classbdm_1_1KalmanCh_48611c8582706cfa62e832be0972e75d}{
133mat \hyperlink{classbdm_1_1KalmanCh_48611c8582706cfa62e832be0972e75d}{preA}}
134\label{classbdm_1_1KalmanCh_48611c8582706cfa62e832be0972e75d}
135
136\begin{CompactList}\small\item\em pre array (triangular matrix) \item\end{CompactList}\item 
137\hypertarget{classbdm_1_1KalmanCh_bcbd68f51d4b57246e7784ca5900171f}{
138mat \hyperlink{classbdm_1_1KalmanCh_bcbd68f51d4b57246e7784ca5900171f}{postA}}
139\label{classbdm_1_1KalmanCh_bcbd68f51d4b57246e7784ca5900171f}
140
141\begin{CompactList}\small\item\em post array (triangular matrix) \item\end{CompactList}\item 
142\hypertarget{classbdm_1_1Kalman_3fe475a1e920b20b63bb342c0e1571f7}{
143RV \hyperlink{classbdm_1_1Kalman_3fe475a1e920b20b63bb342c0e1571f7}{rvy}}
144\label{classbdm_1_1Kalman_3fe475a1e920b20b63bb342c0e1571f7}
145
146\begin{CompactList}\small\item\em Indetifier of output rv. \item\end{CompactList}\item 
147\hypertarget{classbdm_1_1Kalman_149e27424fd1a7cc1c998ea088618a94}{
148RV \hyperlink{classbdm_1_1Kalman_149e27424fd1a7cc1c998ea088618a94}{rvu}}
149\label{classbdm_1_1Kalman_149e27424fd1a7cc1c998ea088618a94}
150
151\begin{CompactList}\small\item\em Indetifier of exogeneous rv. \item\end{CompactList}\item 
152\hypertarget{classbdm_1_1Kalman_ba7699cdb3b1382a54d3e28b9b7517fa}{
153int \hyperlink{classbdm_1_1Kalman_ba7699cdb3b1382a54d3e28b9b7517fa}{dimx}}
154\label{classbdm_1_1Kalman_ba7699cdb3b1382a54d3e28b9b7517fa}
155
156\begin{CompactList}\small\item\em cache of rv.count() \item\end{CompactList}\item 
157\hypertarget{classbdm_1_1Kalman_d2c36ba01760bf207b985bf321b7817f}{
158int \hyperlink{classbdm_1_1Kalman_d2c36ba01760bf207b985bf321b7817f}{dimy}}
159\label{classbdm_1_1Kalman_d2c36ba01760bf207b985bf321b7817f}
160
161\begin{CompactList}\small\item\em cache of rvy.count() \item\end{CompactList}\item 
162\hypertarget{classbdm_1_1Kalman_c5136ef617f6ac0e426bea222755d92b}{
163int \hyperlink{classbdm_1_1Kalman_c5136ef617f6ac0e426bea222755d92b}{dimu}}
164\label{classbdm_1_1Kalman_c5136ef617f6ac0e426bea222755d92b}
165
166\begin{CompactList}\small\item\em cache of rvu.count() \item\end{CompactList}\item 
167\hypertarget{classbdm_1_1Kalman_0a2072e2090c10fac74ad30a023a4ace}{
168mat \hyperlink{classbdm_1_1Kalman_0a2072e2090c10fac74ad30a023a4ace}{A}}
169\label{classbdm_1_1Kalman_0a2072e2090c10fac74ad30a023a4ace}
170
171\begin{CompactList}\small\item\em Matrix A. \item\end{CompactList}\item 
172\hypertarget{classbdm_1_1Kalman_5977b2c81857948a35105f0e7840203c}{
173mat \hyperlink{classbdm_1_1Kalman_5977b2c81857948a35105f0e7840203c}{B}}
174\label{classbdm_1_1Kalman_5977b2c81857948a35105f0e7840203c}
175
176\begin{CompactList}\small\item\em Matrix B. \item\end{CompactList}\item 
177\hypertarget{classbdm_1_1Kalman_818eba63a23972786a4579ad30294177}{
178mat \hyperlink{classbdm_1_1Kalman_818eba63a23972786a4579ad30294177}{C}}
179\label{classbdm_1_1Kalman_818eba63a23972786a4579ad30294177}
180
181\begin{CompactList}\small\item\em Matrix C. \item\end{CompactList}\item 
182\hypertarget{classbdm_1_1Kalman_7b56ac423d0654b5755e4f852a870456}{
183mat \hyperlink{classbdm_1_1Kalman_7b56ac423d0654b5755e4f852a870456}{D}}
184\label{classbdm_1_1Kalman_7b56ac423d0654b5755e4f852a870456}
185
186\begin{CompactList}\small\item\em Matrix D. \item\end{CompactList}\item 
187\hypertarget{classbdm_1_1Kalman_70f8bf19e81b532c60fd3a7a152425ee}{
188\hyperlink{classchmat}{chmat} \hyperlink{classbdm_1_1Kalman_70f8bf19e81b532c60fd3a7a152425ee}{Q}}
189\label{classbdm_1_1Kalman_70f8bf19e81b532c60fd3a7a152425ee}
190
191\begin{CompactList}\small\item\em Matrix Q in square-root form. \item\end{CompactList}\item 
192\hypertarget{classbdm_1_1Kalman_475b088287cdfbba4dc60a3d027728b7}{
193\hyperlink{classchmat}{chmat} \hyperlink{classbdm_1_1Kalman_475b088287cdfbba4dc60a3d027728b7}{R}}
194\label{classbdm_1_1Kalman_475b088287cdfbba4dc60a3d027728b7}
195
196\begin{CompactList}\small\item\em Matrix R in square-root form. \item\end{CompactList}\item 
197\hypertarget{classbdm_1_1Kalman_383f329ff18bbe219254c8b3b916f40d}{
198enorm$<$ \hyperlink{classchmat}{chmat} $>$ \hyperlink{classbdm_1_1Kalman_383f329ff18bbe219254c8b3b916f40d}{est}}
199\label{classbdm_1_1Kalman_383f329ff18bbe219254c8b3b916f40d}
200
201\begin{CompactList}\small\item\em posterior density on \$x\_\-t\$ \item\end{CompactList}\item 
202\hypertarget{classbdm_1_1Kalman_ba555c394c429f6831c9bbabfa2c944c}{
203enorm$<$ \hyperlink{classchmat}{chmat} $>$ \hyperlink{classbdm_1_1Kalman_ba555c394c429f6831c9bbabfa2c944c}{fy}}
204\label{classbdm_1_1Kalman_ba555c394c429f6831c9bbabfa2c944c}
205
206\begin{CompactList}\small\item\em preditive density on \$y\_\-t\$ \item\end{CompactList}\item 
207\hypertarget{classbdm_1_1Kalman_bd69dfb802465f22dd84d73a180d5c92}{
208mat \hyperlink{classbdm_1_1Kalman_bd69dfb802465f22dd84d73a180d5c92}{\_\-K}}
209\label{classbdm_1_1Kalman_bd69dfb802465f22dd84d73a180d5c92}
210
211\begin{CompactList}\small\item\em placeholder for Kalman gain \item\end{CompactList}\item 
212\hypertarget{classbdm_1_1Kalman_c249d45258c8578b13858ad3e7b729b1}{
213vec \& \hyperlink{classbdm_1_1Kalman_c249d45258c8578b13858ad3e7b729b1}{\_\-yp}}
214\label{classbdm_1_1Kalman_c249d45258c8578b13858ad3e7b729b1}
215
216\begin{CompactList}\small\item\em cache of fy.mu \item\end{CompactList}\item 
217\hypertarget{classbdm_1_1Kalman_2dd268f2d7fbe6382cb8825a1114192a}{
218\hyperlink{classchmat}{chmat} \& \hyperlink{classbdm_1_1Kalman_2dd268f2d7fbe6382cb8825a1114192a}{\_\-Ry}}
219\label{classbdm_1_1Kalman_2dd268f2d7fbe6382cb8825a1114192a}
220
221\begin{CompactList}\small\item\em cache of fy.R \item\end{CompactList}\item 
222\hypertarget{classbdm_1_1Kalman_fa172078091e45561343fa513dd573b0}{
223vec \& \hyperlink{classbdm_1_1Kalman_fa172078091e45561343fa513dd573b0}{\_\-mu}}
224\label{classbdm_1_1Kalman_fa172078091e45561343fa513dd573b0}
225
226\begin{CompactList}\small\item\em cache of est.mu \item\end{CompactList}\item 
227\hypertarget{classbdm_1_1Kalman_00c27b0bf324f0018497921ca23c71ed}{
228\hyperlink{classchmat}{chmat} \& \hyperlink{classbdm_1_1Kalman_00c27b0bf324f0018497921ca23c71ed}{\_\-P}}
229\label{classbdm_1_1Kalman_00c27b0bf324f0018497921ca23c71ed}
230
231\begin{CompactList}\small\item\em cache of est.R \item\end{CompactList}\item 
232\hypertarget{classbdm_1_1BM_18d6db4af8ee42077741d9e3618153ca}{
233RV \hyperlink{classbdm_1_1BM_18d6db4af8ee42077741d9e3618153ca}{rv}}
234\label{classbdm_1_1BM_18d6db4af8ee42077741d9e3618153ca}
235
236\begin{CompactList}\small\item\em Random variable of the posterior. \item\end{CompactList}\item 
237\hypertarget{classbdm_1_1BM_4064b6559d962633e4372b12f4cd204a}{
238double \hyperlink{classbdm_1_1BM_4064b6559d962633e4372b12f4cd204a}{ll}}
239\label{classbdm_1_1BM_4064b6559d962633e4372b12f4cd204a}
240
241\begin{CompactList}\small\item\em Logarithm of marginalized data likelihood. \item\end{CompactList}\item 
242\hypertarget{classbdm_1_1BM_faff0ad12556fe7dc0e2807d4fd938ee}{
243bool \hyperlink{classbdm_1_1BM_faff0ad12556fe7dc0e2807d4fd938ee}{evalll}}
244\label{classbdm_1_1BM_faff0ad12556fe7dc0e2807d4fd938ee}
245
246\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 
247\hypertarget{classbdm_1_1BMcond_9a12750776d977408aada06a70093297}{
248RV \hyperlink{classbdm_1_1BMcond_9a12750776d977408aada06a70093297}{rvc}}
249\label{classbdm_1_1BMcond_9a12750776d977408aada06a70093297}
250
251\begin{CompactList}\small\item\em Identificator of the conditioning variable. \item\end{CompactList}\end{CompactItemize}
252
253
254\subsection{Detailed Description}
255Extended Kalman filter with unknown {\tt Q} and delta u.
256
257\subsection{Member Function Documentation}
258\hypertarget{classbdm_1_1BM_50257e0c1e5b5c73153ea6e716ad8ae0}{
259\index{EKFCh\_\-du\_\-kQ@{EKFCh\_\-du\_\-kQ}!logpred@{logpred}}
260\index{logpred@{logpred}!EKFCh_du_kQ@{EKFCh\_\-du\_\-kQ}}
261\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{]}}}}
262\label{classbdm_1_1BM_50257e0c1e5b5c73153ea6e716ad8ae0}
263
264
265Evaluates predictive log-likelihood of the given data record I.e. marginal likelihood of the data with the posterior integrated out.
266
267Reimplemented in \hyperlink{classbdm_1_1ARX_080a7e531e3aa06694112863b15bc6a4}{bdm::ARX}, \hyperlink{classbdm_1_1MixEF_da724da464a75e07521941e430929efa}{bdm::MixEF}, and \hyperlink{classbdm_1_1multiBM_e157b607c1e3fa91d42aeea44458e2bf}{bdm::multiBM}.
268
269Referenced by bdm::BM::logpred\_\-m().\hypertarget{classbdm_1_1BM_3efb3098172f1f67564a312fe732473e}{
270\index{EKFCh\_\-du\_\-kQ@{EKFCh\_\-du\_\-kQ}!\_\-copy\_\-@{\_\-copy\_\-}}
271\index{\_\-copy\_\-@{\_\-copy\_\-}!EKFCh_du_kQ@{EKFCh\_\-du\_\-kQ}}
272\subsubsection[\_\-copy\_\-]{\setlength{\rightskip}{0pt plus 5cm}virtual BM$\ast$ bdm::BM::\_\-copy\_\- (bool {\em changerv} = {\tt false})\hspace{0.3cm}{\tt  \mbox{[}inline, virtual, inherited\mbox{]}}}}
273\label{classbdm_1_1BM_3efb3098172f1f67564a312fe732473e}
274
275
276Copy function required in vectors, Arrays of \hyperlink{classbdm_1_1BM}{BM} etc. Have to be DELETED manually! Prototype: BM$\ast$ \hyperlink{classbdm_1_1BM_3efb3098172f1f67564a312fe732473e}{\_\-copy\_\-()}\{\hyperlink{classbdm_1_1BM}{BM} Tmp$\ast$=new Tmp(this$\ast$); return Tmp; \} 
277
278Reimplemented in \hyperlink{classbdm_1_1ARX_20ff2de8d862f28de7da83444d65bcdb}{bdm::ARX}, and \hyperlink{classbdm_1_1BMEF_5912dbcf28ae711e30b08c2fa766a3e6}{bdm::BMEF}.
279
280The documentation for this class was generated from the following file:\begin{CompactItemize}
281\item 
282work/git/mixpp/pmsm/\hyperlink{mpf__u__delta_8cpp}{mpf\_\-u\_\-delta.cpp}\end{CompactItemize}
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