[30] | 1 | \section{EKF$<$ sq\_\-T $>$ Class Template Reference} |
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| 2 | \label{classEKF}\index{EKF@{EKF}} |
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| 3 | Extended \doxyref{Kalman}{p.}{classKalman} Filter. |
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| 4 | |
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| 5 | |
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| 6 | {\tt \#include $<$libKF.h$>$} |
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| 7 | |
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| 8 | Inheritance diagram for EKF$<$ sq\_\-T $>$:\nopagebreak |
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| 9 | \begin{figure}[H] |
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| 10 | \begin{center} |
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| 11 | \leavevmode |
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| 12 | \includegraphics[width=101pt]{classEKF__inherit__graph} |
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| 13 | \end{center} |
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| 14 | \end{figure} |
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| 15 | Collaboration diagram for EKF$<$ sq\_\-T $>$:\nopagebreak |
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| 16 | \begin{figure}[H] |
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| 17 | \begin{center} |
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| 18 | \leavevmode |
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| 19 | \includegraphics[width=400pt]{classEKF__coll__graph} |
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| 20 | \end{center} |
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| 21 | \end{figure} |
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| 22 | \subsection*{Public Member Functions} |
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| 23 | \begin{CompactItemize} |
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| 24 | \item |
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| 25 | {\bf EKF} ({\bf RV} rvx, {\bf RV} rvy, {\bf RV} rvu)\label{classEKF_ea4f3254cacf0a92d2a820b1201d049e} |
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| 26 | |
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| 27 | \begin{CompactList}\small\item\em Default constructor. \item\end{CompactList}\item |
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| 28 | void \textbf{set\_\-parameters} ({\bf diffbifn} $\ast$pfxu, {\bf diffbifn} $\ast$phxu, const sq\_\-T Q0, const sq\_\-T R0)\label{classEKF_28d058ae4d24d992d2f055419a06ee66} |
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| 29 | |
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| 30 | \item |
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| 31 | void {\bf bayes} (const vec \&dt)\label{classEKF_c79c62c9b3e0b56b3aaa1b6f1d9a7af7} |
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| 32 | |
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| 33 | \begin{CompactList}\small\item\em Here dt = [yt;ut] of appropriate dimensions. \item\end{CompactList}\item |
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| 34 | void {\bf set\_\-parameters} (const mat \&A0, const mat \&B0, const mat \&C0, const mat \&D0, const ldmat \&R0, const ldmat \&Q0)\label{classKalman_239b28a0380946f5749b2f8d2807f93a} |
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| 35 | |
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| 36 | \begin{CompactList}\small\item\em Set parameters with check of relevance. \item\end{CompactList}\item |
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| 37 | void {\bf set\_\-est} (const vec \&mu0, const ldmat \&P0)\label{classKalman_80bcf29466d9a9dd2b8f74699807d0c0} |
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| 38 | |
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| 39 | \begin{CompactList}\small\item\em Set estimate values, used e.g. in initialization. \item\end{CompactList}\item |
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| 40 | void {\bf bayes} (mat Dt)\label{classBM_87b07867fd4c133aa89a18543f68d9f9} |
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| 41 | |
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| 42 | \begin{CompactList}\small\item\em Batch Bayes rule (columns of Dt are observations). \item\end{CompactList}\item |
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| 43 | {\bf epdf} \& {\bf \_\-epdf} ()\label{classKalman_a213c57aef55b2645e550bed81cfc0d4} |
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| 44 | |
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| 45 | \begin{CompactList}\small\item\em Returns a pointer to the \doxyref{epdf}{p.}{classepdf} representing posterior density on parameters. Use with care! \item\end{CompactList}\end{CompactItemize} |
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| 46 | \subsection*{Protected Attributes} |
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| 47 | \begin{CompactItemize} |
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| 48 | \item |
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| 49 | {\bf RV} \textbf{rvy}\label{classKalman_7501230c2fafa3655887d2da23b3184c} |
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| 50 | |
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| 51 | \item |
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| 52 | {\bf RV} \textbf{rvu}\label{classKalman_44a16ffd5ac1e6e39bae34fea9e1e498} |
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| 53 | |
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| 54 | \item |
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| 55 | int \textbf{dimx}\label{classKalman_39c8c403b46fa3b8c7da77cb2e3729eb} |
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| 56 | |
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| 57 | \item |
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| 58 | int \textbf{dimy}\label{classKalman_ba17b956df1e38b31fbbc299c8213b6a} |
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| 59 | |
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| 60 | \item |
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| 61 | int \textbf{dimu}\label{classKalman_b0153795a1444b6968a86409c778d9ce} |
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| 62 | |
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| 63 | \item |
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| 64 | mat \textbf{A}\label{classKalman_5e02efe86ee91e9c74b93b425fe060b9} |
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| 65 | |
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| 66 | \item |
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| 67 | mat \textbf{B}\label{classKalman_dc87704284a6c0bca13bf51f4345a50a} |
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| 68 | |
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| 69 | \item |
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| 70 | mat \textbf{C}\label{classKalman_86a805cd6515872d1132ad0d6eb5dc13} |
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| 71 | |
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| 72 | \item |
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| 73 | mat \textbf{D}\label{classKalman_d69f774ba3335c970c1c5b1d182f4dd1} |
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| 74 | |
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| 75 | \item |
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| 76 | ldmat \textbf{R}\label{classKalman_11d171dc0e0ab111c56a70f98b97b3ec} |
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| 77 | |
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| 78 | \item |
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| 79 | ldmat \textbf{Q}\label{classKalman_9b69015c800eb93f3ee49da23a6f55d9} |
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| 80 | |
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| 81 | \item |
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| 82 | {\bf enorm}$<$ ldmat $>$ {\bf est}\label{classKalman_5568c74bac67ae6d3b1061dba60c9424} |
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| 83 | |
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| 84 | \begin{CompactList}\small\item\em posterior density on \$x\_\-t\$ \item\end{CompactList}\item |
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| 85 | {\bf enorm}$<$ ldmat $>$ {\bf fy}\label{classKalman_e580ab06483952bd03f2e651763e184f} |
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| 86 | |
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| 87 | \begin{CompactList}\small\item\em preditive density on \$y\_\-t\$ \item\end{CompactList}\item |
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| 88 | mat \textbf{\_\-K}\label{classKalman_d422f51467c7a06174af2476d2826132} |
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| 89 | |
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| 90 | \item |
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| 91 | vec $\ast$ \textbf{\_\-yp}\label{classKalman_5188eb0329f8561f0b357af329769bf8} |
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| 92 | |
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| 93 | \item |
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| 94 | ldmat $\ast$ \textbf{\_\-Ry}\label{classKalman_e17dd745daa8a958035a334a56fa4674} |
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| 95 | |
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| 96 | \item |
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| 97 | ldmat $\ast$ \textbf{\_\-iRy}\label{classKalman_fbbdf31365f5a5674099599200ea193b} |
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| 98 | |
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| 99 | \item |
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| 100 | vec $\ast$ \textbf{\_\-mu}\label{classKalman_d1f669b5b3421a070cc75d77b55ba734} |
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| 101 | |
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| 102 | \item |
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| 103 | ldmat $\ast$ \textbf{\_\-P}\label{classKalman_b3388218567128a797e69b109138271d} |
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| 104 | |
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| 105 | \item |
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| 106 | ldmat $\ast$ \textbf{\_\-iP}\label{classKalman_b8bb7f870d69993493ba67ce40e7c3e9} |
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| 107 | |
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| 108 | \item |
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| 109 | {\bf RV} {\bf rv}\label{classBM_af00f0612fabe66241dd507188cdbf88} |
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| 110 | |
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| 111 | \begin{CompactList}\small\item\em Random variable of the posterior. \item\end{CompactList}\item |
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| 112 | double {\bf ll}\label{classBM_5623fef6572a08c2b53b8c87b82dc979} |
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| 113 | |
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| 114 | \begin{CompactList}\small\item\em Logarithm of marginalized data likelihood. \item\end{CompactList}\item |
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| 115 | bool {\bf evalll}\label{classBM_bf6fb59b30141074f8ee1e2f43d03129} |
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| 116 | |
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| 117 | \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}\end{CompactItemize} |
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| 118 | |
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| 119 | |
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| 120 | \subsection{Detailed Description} |
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| 121 | \subsubsection*{template$<$class sq\_\-T$>$ class EKF$<$ sq\_\-T $>$} |
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| 122 | |
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| 123 | Extended \doxyref{Kalman}{p.}{classKalman} Filter. |
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| 124 | |
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| 125 | An approximation of the exact Bayesian filter with Gaussian noices and non-linear evolutions of their mean. |
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| 126 | |
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| 127 | The documentation for this class was generated from the following file:\begin{CompactItemize} |
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| 128 | \item |
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| 129 | work/mixpp/bdm/estim/{\bf libKF.h}\end{CompactItemize} |
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