1 | \section{EKF\_\-unQ Class Reference} |
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2 | \label{classEKF__unQ}\index{EKF\_\-unQ@{EKF\_\-unQ}} |
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3 | Extended \doxyref{Kalman}{p.}{classKalman} filter with unknown {\tt Q}. |
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4 | |
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5 | |
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6 | Inheritance diagram for EKF\_\-unQ:\nopagebreak |
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7 | \begin{figure}[H] |
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8 | \begin{center} |
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9 | \leavevmode |
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10 | \includegraphics[width=95pt]{classEKF__unQ__inherit__graph} |
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11 | \end{center} |
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12 | \end{figure} |
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13 | Collaboration diagram for EKF\_\-unQ:\nopagebreak |
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14 | \begin{figure}[H] |
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15 | \begin{center} |
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16 | \leavevmode |
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17 | \includegraphics[width=400pt]{classEKF__unQ__coll__graph} |
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18 | \end{center} |
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19 | \end{figure} |
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20 | \subsection*{Public Member Functions} |
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21 | \begin{CompactItemize} |
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22 | \item |
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23 | {\bf EKF\_\-unQ} ({\bf RV} rx, {\bf RV} ry, {\bf RV} ru, {\bf RV} rQ)\label{classEKF__unQ_159eaaa5a05c5ceecdaa20956a307244} |
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24 | |
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25 | \begin{CompactList}\small\item\em Default constructor. \item\end{CompactList}\item |
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26 | void {\bf condition} (const vec \&Q0)\label{classEKF__unQ_cd06a8c662da244cf61bb5bd39688c99} |
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27 | |
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28 | \begin{CompactList}\small\item\em Substitute {\tt val} for {\tt rvc}. \item\end{CompactList}\item |
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29 | {\bf EKF\_\-unQ} ({\bf RV} rx, {\bf RV} ry, {\bf RV} ru, {\bf RV} rQ)\label{classEKF__unQ_159eaaa5a05c5ceecdaa20956a307244} |
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30 | |
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31 | \begin{CompactList}\small\item\em Default constructor. \item\end{CompactList}\item |
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32 | void {\bf condition} (const vec \&Q0)\label{classEKF__unQ_cd06a8c662da244cf61bb5bd39688c99} |
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33 | |
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34 | \begin{CompactList}\small\item\em Substitute {\tt val} for {\tt rvc}. \item\end{CompactList}\item |
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35 | void \textbf{bayes} (const vec dt)\label{classEKF__unQ_44b49058c8eb27c7910ae31a1dfd3d21} |
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36 | |
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37 | \item |
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38 | {\bf EKF\_\-unQ} ({\bf RV} rx, {\bf RV} ry, {\bf RV} ru, {\bf RV} rQ)\label{classEKF__unQ_159eaaa5a05c5ceecdaa20956a307244} |
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39 | |
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40 | \begin{CompactList}\small\item\em Default constructor. \item\end{CompactList}\item |
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41 | void {\bf condition} (const vec \&Q0)\label{classEKF__unQ_cd06a8c662da244cf61bb5bd39688c99} |
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42 | |
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43 | \begin{CompactList}\small\item\em Substitute {\tt val} for {\tt rvc}. \item\end{CompactList}\item |
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44 | void {\bf set\_\-parameters} ({\bf diffbifn} $\ast$pfxu, {\bf diffbifn} $\ast$phxu, const {\bf chmat} Q0, const {\bf chmat} R0)\label{classEKFCh_0216bed270df59fe65d0d62d41f8257c} |
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45 | |
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46 | \begin{CompactList}\small\item\em Set nonlinear functions for mean values and covariance matrices. \item\end{CompactList}\item |
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47 | void {\bf set\_\-parameters} (const mat \&A0, const mat \&B0, const mat \&C0, const mat \&D0, const {\bf chmat} \&R0, const {\bf chmat} \&Q0)\label{classKalmanCh_92fb227287af05c9f0078d523c7c9793} |
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48 | |
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49 | \begin{CompactList}\small\item\em Set parameters with check of relevance. \item\end{CompactList}\item |
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50 | void {\bf bayes} (const vec \&dt)\label{classEKFCh_96f6edda324a0b7ef8b4e86cc7af60c1} |
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51 | |
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52 | \begin{CompactList}\small\item\em Here dt = [yt;ut] of appropriate dimensions. \item\end{CompactList}\item |
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53 | void {\bf bayes} (mat Dt)\label{classBM_87b07867fd4c133aa89a18543f68d9f9} |
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54 | |
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55 | \begin{CompactList}\small\item\em Batch Bayes rule (columns of Dt are observations). \item\end{CompactList}\item |
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56 | void {\bf set\_\-est} (const vec \&mu0, const {\bf chmat} \&P0)\label{classKalmanCh_b261b20f6210d4c85131d33302df0adc} |
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57 | |
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58 | \begin{CompactList}\small\item\em Set estimate values, used e.g. in initialization. \item\end{CompactList}\item |
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59 | {\bf epdf} \& {\bf \_\-epdf} ()\label{classKalman_a213c57aef55b2645e550bed81cfc0d4} |
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60 | |
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61 | \begin{CompactList}\small\item\em access function \item\end{CompactList}\item |
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62 | mat \& {\bf \_\-\_\-K} ()\label{classKalman_980fcd41c6c548c5da7b8b67c8e6da79} |
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63 | |
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64 | \begin{CompactList}\small\item\em access function \item\end{CompactList}\item |
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65 | vec {\bf \_\-dP} ()\label{classKalman_ac9540f3850b74d89a5fe4db6fc358ce} |
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66 | |
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67 | \begin{CompactList}\small\item\em access function \item\end{CompactList}\item |
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68 | const {\bf RV} \& {\bf \_\-rv} () const \label{classBM_126bd2595c48e311fc2a7ab72876092a} |
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69 | |
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70 | \begin{CompactList}\small\item\em access function \item\end{CompactList}\item |
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71 | double {\bf \_\-ll} () const \label{classBM_87f4a547d2c29180be88175e5eab9c88} |
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72 | |
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73 | \begin{CompactList}\small\item\em access function \item\end{CompactList}\item |
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74 | const {\bf RV} \& {\bf \_\-rvc} () const \label{classBMcond_3fa60348b2da6b4208bb95b8d146900a} |
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75 | |
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76 | \begin{CompactList}\small\item\em access function \item\end{CompactList}\end{CompactItemize} |
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77 | \subsection*{Protected Attributes} |
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78 | \begin{CompactItemize} |
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79 | \item |
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80 | mat {\bf preA}\label{classKalmanCh_94ee9da75b0e0f632e4a354988ca3798} |
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81 | |
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82 | \begin{CompactList}\small\item\em pre array (triangular matrix) \item\end{CompactList}\item |
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83 | mat {\bf postA}\label{classKalmanCh_0d31a26dc72b5846cfe5af3ccb63ac87} |
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84 | |
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85 | \begin{CompactList}\small\item\em post array (triangular matrix) \item\end{CompactList}\item |
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86 | {\bf RV} {\bf rvy}\label{classKalman_7501230c2fafa3655887d2da23b3184c} |
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87 | |
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88 | \begin{CompactList}\small\item\em Indetifier of output rv. \item\end{CompactList}\item |
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89 | {\bf RV} {\bf rvu}\label{classKalman_44a16ffd5ac1e6e39bae34fea9e1e498} |
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90 | |
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91 | \begin{CompactList}\small\item\em Indetifier of exogeneous rv. \item\end{CompactList}\item |
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92 | int {\bf dimx}\label{classKalman_39c8c403b46fa3b8c7da77cb2e3729eb} |
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93 | |
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94 | \begin{CompactList}\small\item\em cache of rv.count() \item\end{CompactList}\item |
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95 | int {\bf dimy}\label{classKalman_ba17b956df1e38b31fbbc299c8213b6a} |
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96 | |
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97 | \begin{CompactList}\small\item\em cache of rvy.count() \item\end{CompactList}\item |
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98 | int {\bf dimu}\label{classKalman_b0153795a1444b6968a86409c778d9ce} |
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99 | |
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100 | \begin{CompactList}\small\item\em cache of rvu.count() \item\end{CompactList}\item |
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101 | mat {\bf A}\label{classKalman_5e02efe86ee91e9c74b93b425fe060b9} |
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102 | |
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103 | \begin{CompactList}\small\item\em Matrix A. \item\end{CompactList}\item |
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104 | mat {\bf B}\label{classKalman_dc87704284a6c0bca13bf51f4345a50a} |
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105 | |
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106 | \begin{CompactList}\small\item\em Matrix B. \item\end{CompactList}\item |
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107 | mat {\bf C}\label{classKalman_86a805cd6515872d1132ad0d6eb5dc13} |
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108 | |
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109 | \begin{CompactList}\small\item\em Matrix C. \item\end{CompactList}\item |
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110 | mat {\bf D}\label{classKalman_d69f774ba3335c970c1c5b1d182f4dd1} |
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111 | |
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112 | \begin{CompactList}\small\item\em Matrix D. \item\end{CompactList}\item |
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113 | {\bf chmat} {\bf Q}\label{classKalman_9b69015c800eb93f3ee49da23a6f55d9} |
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114 | |
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115 | \begin{CompactList}\small\item\em Matrix Q in square-root form. \item\end{CompactList}\item |
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116 | {\bf chmat} {\bf R}\label{classKalman_11d171dc0e0ab111c56a70f98b97b3ec} |
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117 | |
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118 | \begin{CompactList}\small\item\em Matrix R in square-root form. \item\end{CompactList}\item |
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119 | {\bf enorm}$<$ {\bf chmat} $>$ {\bf est}\label{classKalman_5568c74bac67ae6d3b1061dba60c9424} |
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120 | |
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121 | \begin{CompactList}\small\item\em posterior density on \$x\_\-t\$ \item\end{CompactList}\item |
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122 | {\bf enorm}$<$ {\bf chmat} $>$ {\bf fy}\label{classKalman_e580ab06483952bd03f2e651763e184f} |
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123 | |
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124 | \begin{CompactList}\small\item\em preditive density on \$y\_\-t\$ \item\end{CompactList}\item |
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125 | mat {\bf \_\-K}\label{classKalman_d422f51467c7a06174af2476d2826132} |
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126 | |
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127 | \begin{CompactList}\small\item\em placeholder for \doxyref{Kalman}{p.}{classKalman} gain \item\end{CompactList}\item |
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128 | vec \& {\bf \_\-yp}\label{classKalman_764bbc95238eda11fc81c5ebd0b1dcfd} |
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129 | |
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130 | \begin{CompactList}\small\item\em cache of fy.mu \item\end{CompactList}\item |
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131 | {\bf chmat} \& {\bf \_\-Ry}\label{classKalman_45c9f928d2d62e0c884900fb3380f904} |
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132 | |
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133 | \begin{CompactList}\small\item\em cache of fy.R \item\end{CompactList}\item |
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134 | vec \& {\bf \_\-mu}\label{classKalman_fe803a81d2d847b0b1db3c6b29c18061} |
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135 | |
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136 | \begin{CompactList}\small\item\em cache of est.mu \item\end{CompactList}\item |
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137 | {\bf chmat} \& {\bf \_\-P}\label{classKalman_9fb808cc94a4c2652e1fb93be9bb7dcf} |
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138 | |
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139 | \begin{CompactList}\small\item\em cache of est.R \item\end{CompactList}\item |
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140 | {\bf RV} {\bf rv}\label{classBM_af00f0612fabe66241dd507188cdbf88} |
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141 | |
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142 | \begin{CompactList}\small\item\em Random variable of the posterior. \item\end{CompactList}\item |
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143 | double {\bf ll}\label{classBM_5623fef6572a08c2b53b8c87b82dc979} |
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144 | |
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145 | \begin{CompactList}\small\item\em Logarithm of marginalized data likelihood. \item\end{CompactList}\item |
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146 | bool {\bf evalll}\label{classBM_bf6fb59b30141074f8ee1e2f43d03129} |
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147 | |
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148 | \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 |
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149 | {\bf RV} {\bf rvc}\label{classBMcond_9ba793c8ec453f04d372d17195ed8dec} |
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150 | |
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151 | \begin{CompactList}\small\item\em Identificator of the conditioning variable. \item\end{CompactList}\end{CompactItemize} |
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152 | |
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153 | |
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154 | \subsection{Detailed Description} |
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155 | Extended \doxyref{Kalman}{p.}{classKalman} filter with unknown {\tt Q}. |
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156 | |
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157 | The documentation for this class was generated from the following files:\begin{CompactItemize} |
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158 | \item |
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159 | work/git/mixpp/pmsm/pmsm\_\-sim.cpp\item |
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160 | work/git/mixpp/pmsm/pmsm\_\-sim2.cpp\item |
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161 | work/git/mixpp/pmsm/pmsm\_\-unkQpf.cpp\end{CompactItemize} |
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