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65	<h1>libKF.h</h1><a href="libKF_8h.html">Go to the documentation of this file.</a><div class="fragment"><pre class="fragment"><a name="l00001"></a>00001
66	<a name="l00013"></a>00013 <span class="preprocessor">#ifndef KF_H</span>
67	<a name="l00014"></a>00014 <span class="preprocessor"></span><span class="preprocessor">#define KF_H</span>
68	<a name="l00015"></a>00015 <span class="preprocessor"></span>
69	<a name="l00016"></a>00016
70	<a name="l00017"></a>00017 <span class="preprocessor">#include "../stat/libFN.h"</span>
71	<a name="l00018"></a>00018 <span class="preprocessor">#include "../stat/libEF.h"</span>
72	<a name="l00019"></a>00019 <span class="preprocessor">#include "../math/chmat.h"</span>
73	<a name="l00020"></a>00020 <span class="preprocessor">#include "../user_info.h"</span>
74	<a name="l00021"></a>00021
75	<a name="l00022"></a>00022 <span class="keyword">namespace </span>bdm
76	<a name="l00023"></a>00023 {
77	<a name="l00024"></a>00024
78	<a name="l00029"></a><a class="code" href="classbdm_1_1KalmanFull.html">00029</a> <span class="keyword">class </span><a class="code" href="classbdm_1_1KalmanFull.html" title="Basic Kalman filter with full matrices (education purpose only)! Will be deleted...">KalmanFull</a>
79	<a name="l00030"></a>00030 {
80	<a name="l00031"></a>00031 <span class="keyword">protected</span>:
81	<a name="l00032"></a>00032 <span class="keywordtype">int</span> dimx, dimy, dimu;
82	<a name="l00033"></a>00033 mat A, B, C, D, R, Q;
83	<a name="l00034"></a>00034
84	<a name="l00035"></a>00035 <span class="comment">//cache</span>
85	<a name="l00036"></a>00036 mat _Pp, _Ry, _iRy, _K;
86	<a name="l00037"></a>00037 <span class="keyword">public</span>:
87	<a name="l00038"></a>00038 <span class="comment">//posterior</span>
88	<a name="l00040"></a><a class="code" href="classbdm_1_1KalmanFull.html#2defb75e58892615c5f95fd844f3a666">00040</a> <span class="comment"></span> vec <a class="code" href="classbdm_1_1KalmanFull.html#2defb75e58892615c5f95fd844f3a666" title="Mean value of the posterior density.">mu</a>;
89	<a name="l00042"></a><a class="code" href="classbdm_1_1KalmanFull.html#acacd228e100c3e937de575ad2d7cd9c">00042</a> mat <a class="code" href="classbdm_1_1KalmanFull.html#acacd228e100c3e937de575ad2d7cd9c" title="Variance of the posterior density.">P</a>;
90	<a name="l00043"></a>00043
91	<a name="l00044"></a>00044 <span class="keywordtype">bool</span> evalll;
92	<a name="l00045"></a>00045 <span class="keywordtype">double</span> ll;
93	<a name="l00046"></a>00046 <span class="keyword">public</span>:
94	<a name="l00048"></a>00048 <a class="code" href="classbdm_1_1KalmanFull.html#bdcc98c8b18c1cbdebdf218ae838fd11" title="For EKFfull;.">KalmanFull</a> ( mat A, mat B, mat C, mat D, mat R, mat Q, mat P0, vec mu0 );
95	<a name="l00050"></a>00050 <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1KalmanFull.html#081924bc97f453f674bb982b7951d053" title="Here dt = [yt;ut] of appropriate dimensions.">bayes</a> ( <span class="keyword">const</span> vec &dt );
96	<a name="l00052"></a>00052 <span class="keyword">friend</span> std::ostream &<a class="code" href="classbdm_1_1KalmanFull.html#86ba216243ed95bb46d80d88775d16af" title="print elements of KF">operator<< </a>( std::ostream &os, <span class="keyword">const</span> <a class="code" href="classbdm_1_1KalmanFull.html" title="Basic Kalman filter with full matrices (education purpose only)! Will be deleted...">KalmanFull</a> &kf );
97	<a name="l00054"></a><a class="code" href="classbdm_1_1KalmanFull.html#bdcc98c8b18c1cbdebdf218ae838fd11">00054</a> <a class="code" href="classbdm_1_1KalmanFull.html#bdcc98c8b18c1cbdebdf218ae838fd11" title="For EKFfull;.">KalmanFull</a>() {};
98	<a name="l00055"></a>00055 };
99	<a name="l00056"></a>00056
100	<a name="l00057"></a>00057
101	<a name="l00065"></a>00065 <span class="keyword">template</span><<span class="keyword">class</span> sq_T>
102	<a name="l00066"></a>00066
103	<a name="l00067"></a><a class="code" href="classbdm_1_1Kalman.html">00067</a> <span class="keyword">class </span><a class="code" href="classbdm_1_1Kalman.html" title="Kalman filter with covariance matrices in square root form.">Kalman</a> : <span class="keyword">public</span> <a class="code" href="classbdm_1_1BM.html" title="Bayesian Model of a system, i.e. all uncertainty is modeled by probabilities.">BM</a>
104	<a name="l00068"></a>00068 {
105	<a name="l00069"></a>00069 <span class="keyword">protected</span>:
106	<a name="l00071"></a><a class="code" href="classbdm_1_1Kalman.html#3fe475a1e920b20b63bb342c0e1571f7">00071</a> <a class="code" href="classbdm_1_1RV.html" title="Class representing variables, most often random variables.">RV</a> <a class="code" href="classbdm_1_1Kalman.html#3fe475a1e920b20b63bb342c0e1571f7" title="Indetifier of output rv.">rvy</a>;
107	<a name="l00073"></a><a class="code" href="classbdm_1_1Kalman.html#149e27424fd1a7cc1c998ea088618a94">00073</a> <a class="code" href="classbdm_1_1RV.html" title="Class representing variables, most often random variables.">RV</a> <a class="code" href="classbdm_1_1Kalman.html#149e27424fd1a7cc1c998ea088618a94" title="Indetifier of exogeneous rv.">rvu</a>;
108	<a name="l00075"></a><a class="code" href="classbdm_1_1Kalman.html#ba7699cdb3b1382a54d3e28b9b7517fa">00075</a> <span class="keywordtype">int</span> <a class="code" href="classbdm_1_1Kalman.html#ba7699cdb3b1382a54d3e28b9b7517fa" title="cache of rv.count()">dimx</a>;
109	<a name="l00077"></a><a class="code" href="classbdm_1_1Kalman.html#d2c36ba01760bf207b985bf321b7817f">00077</a> <span class="keywordtype">int</span> <a class="code" href="classbdm_1_1Kalman.html#d2c36ba01760bf207b985bf321b7817f" title="cache of rvy.count()">dimy</a>;
110	<a name="l00079"></a><a class="code" href="classbdm_1_1Kalman.html#c5136ef617f6ac0e426bea222755d92b">00079</a> <span class="keywordtype">int</span> <a class="code" href="classbdm_1_1Kalman.html#c5136ef617f6ac0e426bea222755d92b" title="cache of rvu.count()">dimu</a>;
111	<a name="l00081"></a><a class="code" href="classbdm_1_1Kalman.html#0a2072e2090c10fac74ad30a023a4ace">00081</a> mat <a class="code" href="classbdm_1_1Kalman.html#0a2072e2090c10fac74ad30a023a4ace" title="Matrix A.">A</a>;
112	<a name="l00083"></a><a class="code" href="classbdm_1_1Kalman.html#5977b2c81857948a35105f0e7840203c">00083</a> mat <a class="code" href="classbdm_1_1Kalman.html#5977b2c81857948a35105f0e7840203c" title="Matrix B.">B</a>;
113	<a name="l00085"></a><a class="code" href="classbdm_1_1Kalman.html#818eba63a23972786a4579ad30294177">00085</a> mat <a class="code" href="classbdm_1_1Kalman.html#818eba63a23972786a4579ad30294177" title="Matrix C.">C</a>;
114	<a name="l00087"></a><a class="code" href="classbdm_1_1Kalman.html#7b56ac423d0654b5755e4f852a870456">00087</a> mat <a class="code" href="classbdm_1_1Kalman.html#7b56ac423d0654b5755e4f852a870456" title="Matrix D.">D</a>;
115	<a name="l00089"></a><a class="code" href="classbdm_1_1Kalman.html#70f8bf19e81b532c60fd3a7a152425ee">00089</a> sq_T <a class="code" href="classbdm_1_1Kalman.html#70f8bf19e81b532c60fd3a7a152425ee" title="Matrix Q in square-root form.">Q</a>;
116	<a name="l00091"></a><a class="code" href="classbdm_1_1Kalman.html#475b088287cdfbba4dc60a3d027728b7">00091</a> sq_T <a class="code" href="classbdm_1_1Kalman.html#475b088287cdfbba4dc60a3d027728b7" title="Matrix R in square-root form.">R</a>;
117	<a name="l00092"></a>00092
118	<a name="l00094"></a><a class="code" href="classbdm_1_1Kalman.html#383f329ff18bbe219254c8b3b916f40d">00094</a> <a class="code" href="classbdm_1_1enorm.html" title="Gaussian density with positive definite (decomposed) covariance matrix.">enorm<sq_T></a> <a class="code" href="classbdm_1_1Kalman.html#383f329ff18bbe219254c8b3b916f40d" title="posterior density on $x_t$">est</a>;
119	<a name="l00096"></a><a class="code" href="classbdm_1_1Kalman.html#ba555c394c429f6831c9bbabfa2c944c">00096</a> <a class="code" href="classbdm_1_1enorm.html" title="Gaussian density with positive definite (decomposed) covariance matrix.">enorm<sq_T></a> <a class="code" href="classbdm_1_1Kalman.html#ba555c394c429f6831c9bbabfa2c944c" title="preditive density on $y_t$">fy</a>;
120	<a name="l00097"></a>00097
121	<a name="l00099"></a><a class="code" href="classbdm_1_1Kalman.html#bd69dfb802465f22dd84d73a180d5c92">00099</a> mat <a class="code" href="classbdm_1_1Kalman.html#bd69dfb802465f22dd84d73a180d5c92" title="placeholder for Kalman gain">_K</a>;
122	<a name="l00101"></a><a class="code" href="classbdm_1_1Kalman.html#c249d45258c8578b13858ad3e7b729b1">00101</a> vec& <a class="code" href="classbdm_1_1Kalman.html#c249d45258c8578b13858ad3e7b729b1" title="cache of fy.mu">_yp</a>;
123	<a name="l00103"></a><a class="code" href="classbdm_1_1Kalman.html#2dd268f2d7fbe6382cb8825a1114192a">00103</a> sq_T& <a class="code" href="classbdm_1_1Kalman.html#2dd268f2d7fbe6382cb8825a1114192a" title="cache of fy.R">_Ry</a>;
124	<a name="l00105"></a><a class="code" href="classbdm_1_1Kalman.html#fa172078091e45561343fa513dd573b0">00105</a> vec& <a class="code" href="classbdm_1_1Kalman.html#fa172078091e45561343fa513dd573b0" title="cache of est.mu">_mu</a>;
125	<a name="l00107"></a><a class="code" href="classbdm_1_1Kalman.html#00c27b0bf324f0018497921ca23c71ed">00107</a> sq_T& <a class="code" href="classbdm_1_1Kalman.html#00c27b0bf324f0018497921ca23c71ed" title="cache of est.R">_P</a>;
126	<a name="l00108"></a>00108
127	<a name="l00109"></a>00109 <span class="keyword">public</span>:
128	<a name="l00111"></a>00111 <a class="code" href="classbdm_1_1Kalman.html#025a0196cbcc2e6adb13311f9d3d52b4" title="Default constructor.">Kalman</a> ( );
129	<a name="l00113"></a>00113 <a class="code" href="classbdm_1_1Kalman.html#025a0196cbcc2e6adb13311f9d3d52b4" title="Default constructor.">Kalman</a> ( <span class="keyword">const</span> <a class="code" href="classbdm_1_1Kalman.html" title="Kalman filter with covariance matrices in square root form.">Kalman<sq_T></a> &K0 );
130	<a name="l00115"></a>00115 <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1Kalman.html#3c7fb87fb6b87d08deb6a5a7862da957" title="Set parameters with check of relevance.">set_parameters</a> ( <span class="keyword">const</span> mat &A0,<span class="keyword">const</span> mat &B0,<span class="keyword">const</span> mat &C0,<span class="keyword">const</span> mat &D0,<span class="keyword">const</span> sq_T &Q0,<span class="keyword">const</span> sq_T &R0 );
131	<a name="l00117"></a><a class="code" href="classbdm_1_1Kalman.html#9264fc6b173ecb803d2684b883f32c68">00117</a> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1Kalman.html#9264fc6b173ecb803d2684b883f32c68" title="Set estimate values, used e.g. in initialization.">set_est</a> ( <span class="keyword">const</span> vec &mu0, <span class="keyword">const</span> sq_T &P0 )
132	<a name="l00118"></a>00118 {
133	<a name="l00119"></a>00119 sq_T pom ( <a class="code" href="classbdm_1_1Kalman.html#d2c36ba01760bf207b985bf321b7817f" title="cache of rvy.count()">dimy</a> );
134	<a name="l00120"></a>00120 <a class="code" href="classbdm_1_1Kalman.html#383f329ff18bbe219254c8b3b916f40d" title="posterior density on $x_t$">est</a>.set_parameters ( mu0,P0 );
135	<a name="l00121"></a>00121 P0.mult_sym ( <a class="code" href="classbdm_1_1Kalman.html#818eba63a23972786a4579ad30294177" title="Matrix C.">C</a>,pom );
136	<a name="l00122"></a>00122 <a class="code" href="classbdm_1_1Kalman.html#ba555c394c429f6831c9bbabfa2c944c" title="preditive density on $y_t$">fy</a>.set_parameters ( <a class="code" href="classbdm_1_1Kalman.html#818eba63a23972786a4579ad30294177" title="Matrix C.">C</a>*mu0, pom );
137	<a name="l00123"></a>00123 };
138	<a name="l00124"></a>00124
139	<a name="l00126"></a>00126 <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1Kalman.html#4a39330c14eff8d13179e868a1d1aa8c" title="Here dt = [yt;ut] of appropriate dimensions.">bayes</a> ( <span class="keyword">const</span> vec &dt );
140	<a name="l00128"></a><a class="code" href="classbdm_1_1Kalman.html#f75e487ff6c129d7012d702030f8c890">00128</a> <span class="keyword">const</span> <a class="code" href="classbdm_1_1epdf.html" title="Probability density function with numerical statistics, e.g. posterior density.">epdf</a>& <a class="code" href="classbdm_1_1Kalman.html#f75e487ff6c129d7012d702030f8c890" title="access function">posterior</a>()<span class="keyword"> const </span>{<span class="keywordflow">return</span> <a class="code" href="classbdm_1_1Kalman.html#383f329ff18bbe219254c8b3b916f40d" title="posterior density on $x_t$">est</a>;}
141	<a name="l00129"></a>00129 <span class="keyword">const</span> <a class="code" href="classbdm_1_1enorm.html" title="Gaussian density with positive definite (decomposed) covariance matrix.">enorm<sq_T></a>* _e()<span class="keyword"> const </span>{<span class="keywordflow">return</span> &<a class="code" href="classbdm_1_1Kalman.html#383f329ff18bbe219254c8b3b916f40d" title="posterior density on $x_t$">est</a>;}
142	<a name="l00131"></a><a class="code" href="classbdm_1_1Kalman.html#c788ec6e6c6f5f5861ae8a56d8ede277">00131</a> mat& <a class="code" href="classbdm_1_1Kalman.html#c788ec6e6c6f5f5861ae8a56d8ede277" title="access function">__K</a>() {<span class="keywordflow">return</span> <a class="code" href="classbdm_1_1Kalman.html#bd69dfb802465f22dd84d73a180d5c92" title="placeholder for Kalman gain">_K</a>;}
143	<a name="l00133"></a><a class="code" href="classbdm_1_1Kalman.html#a250d1dbe7bba861dba2a324520cfa48">00133</a> vec <a class="code" href="classbdm_1_1Kalman.html#a250d1dbe7bba861dba2a324520cfa48" title="access function">_dP</a>() {<span class="keywordflow">return</span> <a class="code" href="classbdm_1_1Kalman.html#00c27b0bf324f0018497921ca23c71ed" title="cache of est.R">_P</a>->getD();}
144	<a name="l00134"></a>00134 };
145	<a name="l00135"></a>00135
146	<a name="l00142"></a><a class="code" href="classbdm_1_1KalmanCh.html">00142</a> <span class="keyword">class </span><a class="code" href="classbdm_1_1KalmanCh.html" title="Kalman filter in square root form.">KalmanCh</a> : <span class="keyword">public</span> <a class="code" href="classbdm_1_1Kalman.html" title="Kalman filter with covariance matrices in square root form.">Kalman</a><chmat>
147	<a name="l00143"></a>00143 {
148	<a name="l00144"></a>00144 <span class="keyword">protected</span>:
149	<a name="l00146"></a><a class="code" href="classbdm_1_1KalmanCh.html#48611c8582706cfa62e832be0972e75d">00146</a> mat <a class="code" href="classbdm_1_1KalmanCh.html#48611c8582706cfa62e832be0972e75d" title="pre array (triangular matrix)">preA</a>;
150	<a name="l00148"></a><a class="code" href="classbdm_1_1KalmanCh.html#bcbd68f51d4b57246e7784ca5900171f">00148</a> mat <a class="code" href="classbdm_1_1KalmanCh.html#bcbd68f51d4b57246e7784ca5900171f" title="post array (triangular matrix)">postA</a>;
151	<a name="l00149"></a>00149
152	<a name="l00150"></a>00150 <span class="keyword">public</span>:
153	<a name="l00152"></a><a class="code" href="classbdm_1_1KalmanCh.html#24ce65bdaa538d4d5153d709a929b996">00152</a> <a class="code" href="classbdm_1_1BM.html" title="Bayesian Model of a system, i.e. all uncertainty is modeled by probabilities.">BM</a>* <a class="code" href="classbdm_1_1KalmanCh.html#24ce65bdaa538d4d5153d709a929b996" title="copy constructor">_copy_</a>()<span class="keyword"> const</span>
154	<a name="l00153"></a>00153 <span class="keyword"> </span>{
155	<a name="l00154"></a>00154 <a class="code" href="classbdm_1_1KalmanCh.html" title="Kalman filter in square root form.">KalmanCh</a>* K=<span class="keyword">new</span> <a class="code" href="classbdm_1_1KalmanCh.html" title="Kalman filter in square root form.">KalmanCh</a>;
156	<a name="l00155"></a>00155 K-><a class="code" href="classbdm_1_1KalmanCh.html#20a4d4c664e8ac8a3f1bb7b0d11c6d87" title="Set parameters with check of relevance.">set_parameters</a> ( <a class="code" href="classbdm_1_1Kalman.html#0a2072e2090c10fac74ad30a023a4ace" title="Matrix A.">A</a>,<a class="code" href="classbdm_1_1Kalman.html#5977b2c81857948a35105f0e7840203c" title="Matrix B.">B</a>,<a class="code" href="classbdm_1_1Kalman.html#818eba63a23972786a4579ad30294177" title="Matrix C.">C</a>,<a class="code" href="classbdm_1_1Kalman.html#7b56ac423d0654b5755e4f852a870456" title="Matrix D.">D</a>,<a class="code" href="classbdm_1_1Kalman.html#70f8bf19e81b532c60fd3a7a152425ee" title="Matrix Q in square-root form.">Q</a>,<a class="code" href="classbdm_1_1Kalman.html#475b088287cdfbba4dc60a3d027728b7" title="Matrix R in square-root form.">R</a> );
157	<a name="l00156"></a>00156 K-><a class="code" href="classbdm_1_1KalmanCh.html#6e169272657ed101f3d128b49c59b890">set_statistics</a> ( <a class="code" href="classbdm_1_1Kalman.html#fa172078091e45561343fa513dd573b0" title="cache of est.mu">_mu</a>,<a class="code" href="classbdm_1_1Kalman.html#00c27b0bf324f0018497921ca23c71ed" title="cache of est.R">_P</a> );
158	<a name="l00157"></a>00157 <span class="keywordflow">return</span> K;
159	<a name="l00158"></a>00158 }
160	<a name="l00160"></a>00160 <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1KalmanCh.html#20a4d4c664e8ac8a3f1bb7b0d11c6d87" title="Set parameters with check of relevance.">set_parameters</a> ( <span class="keyword">const</span> mat &A0,<span class="keyword">const</span> mat &B0,<span class="keyword">const</span> mat &C0,<span class="keyword">const</span> mat &D0,<span class="keyword">const</span> <a class="code" href="classchmat.html" title="Symmetric matrix stored in square root decomposition using upper cholesky.">chmat</a> &Q0,<span class="keyword">const</span> <a class="code" href="classchmat.html" title="Symmetric matrix stored in square root decomposition using upper cholesky.">chmat</a> &R0 );
161	<a name="l00161"></a>00161 <span class="keywordtype">void</span> set_statistics ( <span class="keyword">const</span> vec &mu0, <span class="keyword">const</span> <a class="code" href="classchmat.html" title="Symmetric matrix stored in square root decomposition using upper cholesky.">chmat</a> &P0 )
162	<a name="l00162"></a>00162 {
163	<a name="l00163"></a>00163 <a class="code" href="classbdm_1_1Kalman.html#383f329ff18bbe219254c8b3b916f40d" title="posterior density on $x_t$">est</a>.<a class="code" href="classbdm_1_1enorm.html#b8322f2c11560871dd922c660f4771bb">set_parameters</a> ( mu0,P0 );
164	<a name="l00164"></a>00164 };
165	<a name="l00165"></a>00165
166	<a name="l00166"></a>00166
167	<a name="l00180"></a>00180 <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1KalmanCh.html#b41fe5540548100b08e1684c3be767b6" title="Here dt = [yt;ut] of appropriate dimensions.">bayes</a> ( <span class="keyword">const</span> vec &dt );
168	<a name="l00181"></a>00181 };
169	<a name="l00182"></a>00182
170	<a name="l00188"></a><a class="code" href="classbdm_1_1EKFfull.html">00188</a> <span class="keyword">class </span><a class="code" href="classbdm_1_1EKFfull.html" title="Extended Kalman Filter in full matrices.">EKFfull</a> : <span class="keyword">public</span> <a class="code" href="classbdm_1_1KalmanFull.html" title="Basic Kalman filter with full matrices (education purpose only)! Will be deleted...">KalmanFull</a>, <span class="keyword">public</span> <a class="code" href="classbdm_1_1BM.html" title="Bayesian Model of a system, i.e. all uncertainty is modeled by probabilities.">BM</a>
171	<a name="l00189"></a>00189 {
172	<a name="l00190"></a>00190 <span class="keyword">protected</span>:
173	<a name="l00192"></a><a class="code" href="classbdm_1_1EKFfull.html#016d3ec108a430b1e70cf7d78bb963f4">00192</a> <a class="code" href="classbdm_1_1diffbifn.html" title="Class representing a differentiable function of two variables .">diffbifn</a>* <a class="code" href="classbdm_1_1EKFfull.html#016d3ec108a430b1e70cf7d78bb963f4" title="Internal Model f(x,u).">pfxu</a>;
174	<a name="l00194"></a><a class="code" href="classbdm_1_1EKFfull.html#f7cdf9cf74284630b4578a2cb8ba92c7">00194</a> <a class="code" href="classbdm_1_1diffbifn.html" title="Class representing a differentiable function of two variables .">diffbifn</a>* <a class="code" href="classbdm_1_1EKFfull.html#f7cdf9cf74284630b4578a2cb8ba92c7" title="Observation Model h(x,u).">phxu</a>;
175	<a name="l00195"></a>00195
176	<a name="l00196"></a>00196 <a class="code" href="classbdm_1_1enorm.html">enorm<fsqmat></a> E;
177	<a name="l00197"></a>00197 <span class="keyword">public</span>:
178	<a name="l00199"></a>00199 <a class="code" href="classbdm_1_1EKFfull.html#6939c345389abb8b2481457b4cfe1165" title="Default constructor.">EKFfull</a> ( );
179	<a name="l00201"></a>00201 <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1EKFfull.html#78748da361ba61fef162b0d8956d1743" title="Set nonlinear functions for mean values and covariance matrices.">set_parameters</a> ( <a class="code" href="classbdm_1_1diffbifn.html" title="Class representing a differentiable function of two variables .">diffbifn</a>* <a class="code" href="classbdm_1_1EKFfull.html#016d3ec108a430b1e70cf7d78bb963f4" title="Internal Model f(x,u).">pfxu</a>, <a class="code" href="classbdm_1_1diffbifn.html" title="Class representing a differentiable function of two variables .">diffbifn</a>* <a class="code" href="classbdm_1_1EKFfull.html#f7cdf9cf74284630b4578a2cb8ba92c7" title="Observation Model h(x,u).">phxu</a>, <span class="keyword">const</span> mat Q0, <span class="keyword">const</span> mat R0 );
180	<a name="l00203"></a>00203 <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1EKFfull.html#f149ae8e9ce14d9931a7bb2850736699" title="Here dt = [yt;ut] of appropriate dimensions.">bayes</a> ( <span class="keyword">const</span> vec &dt );
181	<a name="l00205"></a><a class="code" href="classbdm_1_1EKFfull.html#1949a9b1496a855cc7c24e619bc52365">00205</a> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1EKFfull.html#1949a9b1496a855cc7c24e619bc52365" title="set estimates">set_statistics</a> ( vec mu0, mat P0 ) {<a class="code" href="classbdm_1_1KalmanFull.html#2defb75e58892615c5f95fd844f3a666" title="Mean value of the posterior density.">mu</a>=mu0;<a class="code" href="classbdm_1_1KalmanFull.html#acacd228e100c3e937de575ad2d7cd9c" title="Variance of the posterior density.">P</a>=P0;};
182	<a name="l00207"></a><a class="code" href="classbdm_1_1EKFfull.html#7e9a69f36a0a0615c9abb806772ef36d">00207</a> <span class="keyword">const</span> <a class="code" href="classbdm_1_1epdf.html" title="Probability density function with numerical statistics, e.g. posterior density.">epdf</a>& <a class="code" href="classbdm_1_1EKFfull.html#7e9a69f36a0a0615c9abb806772ef36d" title="dummy!">posterior</a>()<span class="keyword"> const</span>{<span class="keywordflow">return</span> E;};
183	<a name="l00208"></a>00208 <span class="keyword">const</span> <a class="code" href="classbdm_1_1enorm.html">enorm<fsqmat></a>* _e()<span class="keyword"> const</span>{<span class="keywordflow">return</span> &E;};
184	<a name="l00209"></a>00209 <span class="keyword">const</span> mat _R() {<span class="keywordflow">return</span> <a class="code" href="classbdm_1_1KalmanFull.html#acacd228e100c3e937de575ad2d7cd9c" title="Variance of the posterior density.">P</a>;}
185	<a name="l00210"></a>00210 };
186	<a name="l00211"></a>00211
187	<a name="l00217"></a>00217 <span class="keyword">template</span><<span class="keyword">class</span> sq_T>
188	<a name="l00218"></a><a class="code" href="classbdm_1_1EKF.html">00218</a> <span class="keyword">class </span><a class="code" href="classbdm_1_1EKF.html" title="Extended Kalman Filter.">EKF</a> : <span class="keyword">public</span> <a class="code" href="classbdm_1_1Kalman.html" title="Kalman filter with covariance matrices in square root form.">Kalman</a><fsqmat>
189	<a name="l00219"></a>00219 {
190	<a name="l00221"></a>00221 <a class="code" href="classbdm_1_1diffbifn.html" title="Class representing a differentiable function of two variables .">diffbifn</a>* pfxu;
191	<a name="l00223"></a>00223 <a class="code" href="classbdm_1_1diffbifn.html" title="Class representing a differentiable function of two variables .">diffbifn</a>* phxu;
192	<a name="l00224"></a>00224 <span class="keyword">public</span>:
193	<a name="l00226"></a>00226 <a class="code" href="classbdm_1_1EKF.html#d087a8bb408d26ac4f5c542746b81059" title="Default constructor.">EKF</a> ( <a class="code" href="classbdm_1_1RV.html" title="Class representing variables, most often random variables.">RV</a> rvx, <a class="code" href="classbdm_1_1RV.html" title="Class representing variables, most often random variables.">RV</a> <a class="code" href="classbdm_1_1Kalman.html#3fe475a1e920b20b63bb342c0e1571f7" title="Indetifier of output rv.">rvy</a>, <a class="code" href="classbdm_1_1RV.html" title="Class representing variables, most often random variables.">RV</a> <a class="code" href="classbdm_1_1Kalman.html#149e27424fd1a7cc1c998ea088618a94" title="Indetifier of exogeneous rv.">rvu</a> );
194	<a name="l00228"></a><a class="code" href="classbdm_1_1EKF.html#fe9b2e227255ad32dc73df316b7318f4">00228</a> <a class="code" href="classbdm_1_1EKF.html" title="Extended Kalman Filter.">EKF<sq_T></a>* <a class="code" href="classbdm_1_1EKF.html#fe9b2e227255ad32dc73df316b7318f4" title="copy constructor">_copy_</a>()<span class="keyword"> const </span>{ <span class="keywordflow">return</span> <span class="keyword">new</span> <a class="code" href="classbdm_1_1EKF.html" title="Extended Kalman Filter.">EKF<sq_T></a> ( this ); }
195	<a name="l00230"></a>00230 <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1EKF.html#00fec1a0a6a467eb83fb36c65eba7bcb" title="Set nonlinear functions for mean values and covariance matrices.">set_parameters</a> ( <a class="code" href="classbdm_1_1diffbifn.html" title="Class representing a differentiable function of two variables .">diffbifn</a>* pfxu, <a class="code" href="classbdm_1_1diffbifn.html" title="Class representing a differentiable function of two variables .">diffbifn</a>* phxu, <span class="keyword">const</span> sq_T Q0, <span class="keyword">const</span> sq_T R0 );
196	<a name="l00232"></a>00232 <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1EKF.html#3fb182ecc29b10ca1163cecbf3bcccfa" title="Here dt = [yt;ut] of appropriate dimensions.">bayes</a> ( <span class="keyword">const</span> vec &dt );
197	<a name="l00233"></a>00233 };
198	<a name="l00234"></a>00234
199	<a name="l00241"></a><a class="code" href="classbdm_1_1EKFCh.html">00241</a> <span class="keyword">class </span><a class="code" href="classbdm_1_1EKFCh.html" title="Extended Kalman Filter in Square root.">EKFCh</a> : <span class="keyword">public</span> <a class="code" href="classbdm_1_1KalmanCh.html" title="Kalman filter in square root form.">KalmanCh</a>
200	<a name="l00242"></a>00242 {
201	<a name="l00243"></a>00243 <span class="keyword">protected</span>:
202	<a name="l00245"></a><a class="code" href="classbdm_1_1EKFCh.html#e1e895f994398a55bc425551fc275ba3">00245</a> <a class="code" href="classbdm_1_1diffbifn.html" title="Class representing a differentiable function of two variables .">diffbifn</a>* <a class="code" href="classbdm_1_1EKFCh.html#e1e895f994398a55bc425551fc275ba3" title="Internal Model f(x,u).">pfxu</a>;
203	<a name="l00247"></a><a class="code" href="classbdm_1_1EKFCh.html#6b34c69641826322467b704e8252f317">00247</a> <a class="code" href="classbdm_1_1diffbifn.html" title="Class representing a differentiable function of two variables .">diffbifn</a>* <a class="code" href="classbdm_1_1EKFCh.html#6b34c69641826322467b704e8252f317" title="Observation Model h(x,u).">phxu</a>;
204	<a name="l00248"></a>00248 <span class="keyword">public</span>:
205	<a name="l00250"></a><a class="code" href="classbdm_1_1EKFCh.html#1d1d91400e3f177de9fe7962ea17adc4">00250</a> <a class="code" href="classbdm_1_1BM.html" title="Bayesian Model of a system, i.e. all uncertainty is modeled by probabilities.">BM</a>* <a class="code" href="classbdm_1_1EKFCh.html#1d1d91400e3f177de9fe7962ea17adc4" title="copy constructor duplicated - calls different set_parameters">_copy_</a>()<span class="keyword"> const</span>
206	<a name="l00251"></a>00251 <span class="keyword"> </span>{
207	<a name="l00252"></a>00252 <a class="code" href="classbdm_1_1EKFCh.html" title="Extended Kalman Filter in Square root.">EKFCh</a>* E=<span class="keyword">new</span> <a class="code" href="classbdm_1_1EKFCh.html" title="Extended Kalman Filter in Square root.">EKFCh</a>;
208	<a name="l00253"></a>00253 E-><a class="code" href="classbdm_1_1EKFCh.html#50f9fbffad721f35e5ccb75d0f6b842a" title="Set nonlinear functions for mean values and covariance matrices.">set_parameters</a> ( <a class="code" href="classbdm_1_1EKFCh.html#e1e895f994398a55bc425551fc275ba3" title="Internal Model f(x,u).">pfxu</a>,<a class="code" href="classbdm_1_1EKFCh.html#6b34c69641826322467b704e8252f317" title="Observation Model h(x,u).">phxu</a>,<a class="code" href="classbdm_1_1Kalman.html#70f8bf19e81b532c60fd3a7a152425ee" title="Matrix Q in square-root form.">Q</a>,<a class="code" href="classbdm_1_1Kalman.html#475b088287cdfbba4dc60a3d027728b7" title="Matrix R in square-root form.">R</a> );
209	<a name="l00254"></a>00254 E-><a class="code" href="classbdm_1_1KalmanCh.html#6e169272657ed101f3d128b49c59b890">set_statistics</a> ( <a class="code" href="classbdm_1_1Kalman.html#fa172078091e45561343fa513dd573b0" title="cache of est.mu">_mu</a>,<a class="code" href="classbdm_1_1Kalman.html#00c27b0bf324f0018497921ca23c71ed" title="cache of est.R">_P</a> );
210	<a name="l00255"></a>00255 <span class="keywordflow">return</span> E;
211	<a name="l00256"></a>00256 }
212	<a name="l00258"></a>00258 <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1EKFCh.html#50f9fbffad721f35e5ccb75d0f6b842a" title="Set nonlinear functions for mean values and covariance matrices.">set_parameters</a> ( <a class="code" href="classbdm_1_1diffbifn.html" title="Class representing a differentiable function of two variables .">diffbifn</a>* <a class="code" href="classbdm_1_1EKFCh.html#e1e895f994398a55bc425551fc275ba3" title="Internal Model f(x,u).">pfxu</a>, <a class="code" href="classbdm_1_1diffbifn.html" title="Class representing a differentiable function of two variables .">diffbifn</a>* <a class="code" href="classbdm_1_1EKFCh.html#6b34c69641826322467b704e8252f317" title="Observation Model h(x,u).">phxu</a>, <span class="keyword">const</span> <a class="code" href="classchmat.html" title="Symmetric matrix stored in square root decomposition using upper cholesky.">chmat</a> Q0, <span class="keyword">const</span> <a class="code" href="classchmat.html" title="Symmetric matrix stored in square root decomposition using upper cholesky.">chmat</a> R0 );
213	<a name="l00260"></a>00260 <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1EKFCh.html#4c8609c37290b158f88a31dae4047225" title="Here dt = [yt;ut] of appropriate dimensions.">bayes</a> ( <span class="keyword">const</span> vec &dt );
214	<a name="l00261"></a>00261
215	<a name="l00262"></a>00262 <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1EKFCh.html#0c2d3a9d57f23b998c53d7c12fa2a724" title="This method arrange instance properties according the data stored in the Setting...">from_setting</a>( <span class="keyword">const</span> Setting &root );
216	<a name="l00263"></a>00263
217	<a name="l00264"></a>00264 <span class="comment">// TODO dodelat void to_setting( Setting &root ) const;</span>
218	<a name="l00265"></a>00265
219	<a name="l00266"></a>00266 };
220	<a name="l00267"></a>00267
221	<a name="l00268"></a>00268 UIREGISTER(EKFCh);
222	<a name="l00269"></a>00269
223	<a name="l00270"></a>00270
224	<a name="l00275"></a><a class="code" href="classbdm_1_1KFcondQR.html">00275</a> <span class="keyword">class </span><a class="code" href="classbdm_1_1KFcondQR.html" title="Kalman Filter with conditional diagonal matrices R and Q.">KFcondQR</a> : <span class="keyword">public</span> <a class="code" href="classbdm_1_1Kalman.html" title="Kalman filter with covariance matrices in square root form.">Kalman</a><ldmat>
225	<a name="l00276"></a>00276 {
226	<a name="l00277"></a>00277 <span class="comment">//protected:</span>
227	<a name="l00278"></a>00278 <span class="keyword">public</span>:
228	<a name="l00279"></a><a class="code" href="classbdm_1_1KFcondQR.html#31bc31087ee7ed6c0bfb92d626321b91">00279</a> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1KFcondQR.html#31bc31087ee7ed6c0bfb92d626321b91" title="Substitute val for rvc.">condition</a> ( <span class="keyword">const</span> vec &QR )
229	<a name="l00280"></a>00280 {
230	<a name="l00281"></a>00281 it_assert_debug ( QR.length() == ( <a class="code" href="classbdm_1_1Kalman.html#ba7699cdb3b1382a54d3e28b9b7517fa" title="cache of rv.count()">dimx</a>+<a class="code" href="classbdm_1_1Kalman.html#d2c36ba01760bf207b985bf321b7817f" title="cache of rvy.count()">dimy</a> ),<span class="stringliteral">"KFcondRQ: conditioning by incompatible vector"</span> );
231	<a name="l00282"></a>00282
232	<a name="l00283"></a>00283 <a class="code" href="classbdm_1_1Kalman.html#70f8bf19e81b532c60fd3a7a152425ee" title="Matrix Q in square-root form.">Q</a>.<a class="code" href="classldmat.html#0884a613b94fde61bfc84288e73ce57f" title="Access functions.">setD</a> ( QR ( 0, <a class="code" href="classbdm_1_1Kalman.html#ba7699cdb3b1382a54d3e28b9b7517fa" title="cache of rv.count()">dimx</a>-1 ) );
233	<a name="l00284"></a>00284 <a class="code" href="classbdm_1_1Kalman.html#475b088287cdfbba4dc60a3d027728b7" title="Matrix R in square-root form.">R</a>.<a class="code" href="classldmat.html#0884a613b94fde61bfc84288e73ce57f" title="Access functions.">setD</a> ( QR ( <a class="code" href="classbdm_1_1Kalman.html#ba7699cdb3b1382a54d3e28b9b7517fa" title="cache of rv.count()">dimx</a>, -1 ) );
234	<a name="l00285"></a>00285 };
235	<a name="l00286"></a>00286 };
236	<a name="l00287"></a>00287
237	<a name="l00292"></a><a class="code" href="classbdm_1_1KFcondR.html">00292</a> <span class="keyword">class </span><a class="code" href="classbdm_1_1KFcondR.html" title="Kalman Filter with conditional diagonal matrices R and Q.">KFcondR</a> : <span class="keyword">public</span> <a class="code" href="classbdm_1_1Kalman.html" title="Kalman filter with covariance matrices in square root form.">Kalman</a><ldmat>
238	<a name="l00293"></a>00293 {
239	<a name="l00294"></a>00294 <span class="comment">//protected:</span>
240	<a name="l00295"></a>00295 <span class="keyword">public</span>:
241	<a name="l00297"></a><a class="code" href="classbdm_1_1KFcondR.html#f11639d79f10b1e7dad16a0d8233450d">00297</a> <a class="code" href="classbdm_1_1KFcondR.html#f11639d79f10b1e7dad16a0d8233450d" title="Default constructor.">KFcondR</a> ( ) : <a class="code" href="classbdm_1_1Kalman.html" title="Kalman filter with covariance matrices in square root form.">Kalman</a><<a class="code" href="classldmat.html" title="Matrix stored in LD form, (commonly known as UD).">ldmat</a>> ( ) {};
242	<a name="l00298"></a>00298
243	<a name="l00299"></a><a class="code" href="classbdm_1_1KFcondR.html#7d42a421acbdcf9b610a5682ee5fb9a8">00299</a> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1KFcondR.html#7d42a421acbdcf9b610a5682ee5fb9a8" title="Substitute val for rvc.">condition</a> ( <span class="keyword">const</span> vec &R0 )
244	<a name="l00300"></a>00300 {
245	<a name="l00301"></a>00301 it_assert_debug ( R0.length() == ( <a class="code" href="classbdm_1_1Kalman.html#d2c36ba01760bf207b985bf321b7817f" title="cache of rvy.count()">dimy</a> ),<span class="stringliteral">"KFcondR: conditioning by incompatible vector"</span> );
246	<a name="l00302"></a>00302
247	<a name="l00303"></a>00303 <a class="code" href="classbdm_1_1Kalman.html#475b088287cdfbba4dc60a3d027728b7" title="Matrix R in square-root form.">R</a>.<a class="code" href="classldmat.html#0884a613b94fde61bfc84288e73ce57f" title="Access functions.">setD</a> ( R0 );
248	<a name="l00304"></a>00304 };
249	<a name="l00305"></a>00305
250	<a name="l00306"></a>00306 };
251	<a name="l00307"></a>00307
252	<a name="l00309"></a>00309
253	<a name="l00310"></a>00310 <span class="keyword">template</span><<span class="keyword">class</span> sq_T>
254	<a name="l00311"></a><a class="code" href="classbdm_1_1Kalman.html#8b22c45cffa949d70b8e5ac92ed5ce25">00311</a> <a class="code" href="classbdm_1_1Kalman.html#025a0196cbcc2e6adb13311f9d3d52b4" title="Default constructor.">Kalman<sq_T>::Kalman</a> ( <span class="keyword">const</span> <a class="code" href="classbdm_1_1Kalman.html" title="Kalman filter with covariance matrices in square root form.">Kalman<sq_T></a> &K0 ) : <a class="code" href="classbdm_1_1BM.html" title="Bayesian Model of a system, i.e. all uncertainty is modeled by probabilities.">BM</a> ( ),rvy ( K0.rvy ),rvu ( K0.rvu ),
255	<a name="l00312"></a>00312 dimx ( K0.dimx ), dimy ( K0.dimy ),dimu ( K0.dimu ),
256	<a name="l00313"></a>00313 A ( K0.A ), B ( K0.B ), C ( K0.C ), D ( K0.D ),
257	<a name="l00314"></a>00314 Q ( K0.Q ), R ( K0.R ),
258	<a name="l00315"></a>00315 est ( K0.est ), fy ( K0.fy ), _yp ( fy._mu() ),_Ry ( fy._R() ), _mu ( est._mu() ), _P ( est._R() )
259	<a name="l00316"></a>00316 {
260	<a name="l00317"></a>00317
261	<a name="l00318"></a>00318 <span class="comment">// copy values in pointers</span>
262	<a name="l00319"></a>00319 <span class="comment">// _mu = K0._mu;</span>
263	<a name="l00320"></a>00320 <span class="comment">// _P = K0._P;</span>
264	<a name="l00321"></a>00321 <span class="comment">// _yp = K0._yp;</span>
265	<a name="l00322"></a>00322 <span class="comment">// _Ry = K0._Ry;</span>
266	<a name="l00323"></a>00323
267	<a name="l00324"></a>00324 }
268	<a name="l00325"></a>00325
269	<a name="l00326"></a>00326 <span class="keyword">template</span><<span class="keyword">class</span> sq_T>
270	<a name="l00327"></a><a class="code" href="classbdm_1_1Kalman.html#025a0196cbcc2e6adb13311f9d3d52b4">00327</a> <a class="code" href="classbdm_1_1Kalman.html#025a0196cbcc2e6adb13311f9d3d52b4" title="Default constructor.">Kalman<sq_T>::Kalman</a> ( ) : <a class="code" href="classbdm_1_1BM.html" title="Bayesian Model of a system, i.e. all uncertainty is modeled by probabilities.">BM</a> (), est ( ), fy (), _yp ( fy._mu() ), _Ry ( fy._R() ), _mu ( est._mu() ), _P ( est._R() )
271	<a name="l00328"></a>00328 {
272	<a name="l00329"></a>00329 };
273	<a name="l00330"></a>00330
274	<a name="l00331"></a>00331 <span class="keyword">template</span><<span class="keyword">class</span> sq_T>
275	<a name="l00332"></a><a class="code" href="classbdm_1_1Kalman.html#3c7fb87fb6b87d08deb6a5a7862da957">00332</a> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1Kalman.html#3c7fb87fb6b87d08deb6a5a7862da957" title="Set parameters with check of relevance.">Kalman<sq_T>::set_parameters</a> ( <span class="keyword">const</span> mat &A0,<span class="keyword">const</span> mat &B0, <span class="keyword">const</span> mat &C0, <span class="keyword">const</span> mat &D0, <span class="keyword">const</span> sq_T &Q0, <span class="keyword">const</span> sq_T &R0 )
276	<a name="l00333"></a>00333 {
277	<a name="l00334"></a>00334 <a class="code" href="classbdm_1_1Kalman.html#ba7699cdb3b1382a54d3e28b9b7517fa" title="cache of rv.count()">dimx</a> = A0.rows();
278	<a name="l00335"></a>00335 <a class="code" href="classbdm_1_1Kalman.html#d2c36ba01760bf207b985bf321b7817f" title="cache of rvy.count()">dimy</a> = C0.rows();
279	<a name="l00336"></a>00336 <a class="code" href="classbdm_1_1Kalman.html#c5136ef617f6ac0e426bea222755d92b" title="cache of rvu.count()">dimu</a> = B0.cols();
280	<a name="l00337"></a>00337
281	<a name="l00338"></a>00338 it_assert_debug ( A0.cols() ==<a class="code" href="classbdm_1_1Kalman.html#ba7699cdb3b1382a54d3e28b9b7517fa" title="cache of rv.count()">dimx</a>, <span class="stringliteral">"Kalman: A is not square"</span> );
282	<a name="l00339"></a>00339 it_assert_debug ( B0.rows() ==<a class="code" href="classbdm_1_1Kalman.html#ba7699cdb3b1382a54d3e28b9b7517fa" title="cache of rv.count()">dimx</a>, <span class="stringliteral">"Kalman: B is not compatible"</span> );
283	<a name="l00340"></a>00340 it_assert_debug ( C0.cols() ==<a class="code" href="classbdm_1_1Kalman.html#ba7699cdb3b1382a54d3e28b9b7517fa" title="cache of rv.count()">dimx</a>, <span class="stringliteral">"Kalman: C is not square"</span> );
284	<a name="l00341"></a>00341 it_assert_debug ( ( D0.rows() ==<a class="code" href="classbdm_1_1Kalman.html#d2c36ba01760bf207b985bf321b7817f" title="cache of rvy.count()">dimy</a> ) \|\| ( D0.cols() ==<a class="code" href="classbdm_1_1Kalman.html#c5136ef617f6ac0e426bea222755d92b" title="cache of rvu.count()">dimu</a> ), <span class="stringliteral">"Kalman: D is not compatible"</span> );
285	<a name="l00342"></a>00342 it_assert_debug ( ( R0.cols() ==<a class="code" href="classbdm_1_1Kalman.html#d2c36ba01760bf207b985bf321b7817f" title="cache of rvy.count()">dimy</a> ) \|\| ( R0.rows() ==<a class="code" href="classbdm_1_1Kalman.html#d2c36ba01760bf207b985bf321b7817f" title="cache of rvy.count()">dimy</a> ), <span class="stringliteral">"Kalman: R is not compatible"</span> );
286	<a name="l00343"></a>00343 it_assert_debug ( ( Q0.cols() ==<a class="code" href="classbdm_1_1Kalman.html#ba7699cdb3b1382a54d3e28b9b7517fa" title="cache of rv.count()">dimx</a> ) \|\| ( Q0.rows() ==<a class="code" href="classbdm_1_1Kalman.html#ba7699cdb3b1382a54d3e28b9b7517fa" title="cache of rv.count()">dimx</a> ), <span class="stringliteral">"Kalman: Q is not compatible"</span> );
287	<a name="l00344"></a>00344
288	<a name="l00345"></a>00345 <a class="code" href="classbdm_1_1Kalman.html#0a2072e2090c10fac74ad30a023a4ace" title="Matrix A.">A</a> = A0;
289	<a name="l00346"></a>00346 <a class="code" href="classbdm_1_1Kalman.html#5977b2c81857948a35105f0e7840203c" title="Matrix B.">B</a> = B0;
290	<a name="l00347"></a>00347 <a class="code" href="classbdm_1_1Kalman.html#818eba63a23972786a4579ad30294177" title="Matrix C.">C</a> = C0;
291	<a name="l00348"></a>00348 <a class="code" href="classbdm_1_1Kalman.html#7b56ac423d0654b5755e4f852a870456" title="Matrix D.">D</a> = D0;
292	<a name="l00349"></a>00349 <a class="code" href="classbdm_1_1Kalman.html#475b088287cdfbba4dc60a3d027728b7" title="Matrix R in square-root form.">R</a> = R0;
293	<a name="l00350"></a>00350 <a class="code" href="classbdm_1_1Kalman.html#70f8bf19e81b532c60fd3a7a152425ee" title="Matrix Q in square-root form.">Q</a> = Q0;
294	<a name="l00351"></a>00351 }
295	<a name="l00352"></a>00352
296	<a name="l00353"></a>00353 <span class="keyword">template</span><<span class="keyword">class</span> sq_T>
297	<a name="l00354"></a><a class="code" href="classbdm_1_1Kalman.html#4a39330c14eff8d13179e868a1d1aa8c">00354</a> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1Kalman.html#4a39330c14eff8d13179e868a1d1aa8c" title="Here dt = [yt;ut] of appropriate dimensions.">Kalman<sq_T>::bayes</a> ( <span class="keyword">const</span> vec &dt )
298	<a name="l00355"></a>00355 {
299	<a name="l00356"></a>00356 it_assert_debug ( dt.length() == ( <a class="code" href="classbdm_1_1Kalman.html#d2c36ba01760bf207b985bf321b7817f" title="cache of rvy.count()">dimy</a>+<a class="code" href="classbdm_1_1Kalman.html#c5136ef617f6ac0e426bea222755d92b" title="cache of rvu.count()">dimu</a> ),<span class="stringliteral">"KalmanFull::bayes wrong size of dt"</span> );
300	<a name="l00357"></a>00357
301	<a name="l00358"></a>00358 sq_T iRy ( <a class="code" href="classbdm_1_1Kalman.html#d2c36ba01760bf207b985bf321b7817f" title="cache of rvy.count()">dimy</a> );
302	<a name="l00359"></a>00359 vec u = dt.get ( <a class="code" href="classbdm_1_1Kalman.html#d2c36ba01760bf207b985bf321b7817f" title="cache of rvy.count()">dimy</a>,<a class="code" href="classbdm_1_1Kalman.html#d2c36ba01760bf207b985bf321b7817f" title="cache of rvy.count()">dimy</a>+<a class="code" href="classbdm_1_1Kalman.html#c5136ef617f6ac0e426bea222755d92b" title="cache of rvu.count()">dimu</a>-1 );
303	<a name="l00360"></a>00360 vec y = dt.get ( 0,<a class="code" href="classbdm_1_1Kalman.html#d2c36ba01760bf207b985bf321b7817f" title="cache of rvy.count()">dimy</a>-1 );
304	<a name="l00361"></a>00361 <span class="comment">//Time update</span>
305	<a name="l00362"></a>00362 <a class="code" href="classbdm_1_1Kalman.html#fa172078091e45561343fa513dd573b0" title="cache of est.mu">_mu</a> = <a class="code" href="classbdm_1_1Kalman.html#0a2072e2090c10fac74ad30a023a4ace" title="Matrix A.">A</a>* <a class="code" href="classbdm_1_1Kalman.html#fa172078091e45561343fa513dd573b0" title="cache of est.mu">_mu</a> + <a class="code" href="classbdm_1_1Kalman.html#5977b2c81857948a35105f0e7840203c" title="Matrix B.">B</a>*u;
306	<a name="l00363"></a>00363 <span class="comment">//P = APA.transpose() + Q; in sq_T</span>
307	<a name="l00364"></a>00364 <a class="code" href="classbdm_1_1Kalman.html#00c27b0bf324f0018497921ca23c71ed" title="cache of est.R">_P</a>.mult_sym ( <a class="code" href="classbdm_1_1Kalman.html#0a2072e2090c10fac74ad30a023a4ace" title="Matrix A.">A</a> );
308	<a name="l00365"></a>00365 <a class="code" href="classbdm_1_1Kalman.html#00c27b0bf324f0018497921ca23c71ed" title="cache of est.R">_P</a> +=<a class="code" href="classbdm_1_1Kalman.html#70f8bf19e81b532c60fd3a7a152425ee" title="Matrix Q in square-root form.">Q</a>;
309	<a name="l00366"></a>00366
310	<a name="l00367"></a>00367 <span class="comment">//Data update</span>
311	<a name="l00368"></a>00368 <span class="comment">//_Ry = CPC.transpose() + R; in sq_T</span>
312	<a name="l00369"></a>00369 <a class="code" href="classbdm_1_1Kalman.html#00c27b0bf324f0018497921ca23c71ed" title="cache of est.R">_P</a>.mult_sym ( <a class="code" href="classbdm_1_1Kalman.html#818eba63a23972786a4579ad30294177" title="Matrix C.">C</a>, <a class="code" href="classbdm_1_1Kalman.html#2dd268f2d7fbe6382cb8825a1114192a" title="cache of fy.R">_Ry</a> );
313	<a name="l00370"></a>00370 <a class="code" href="classbdm_1_1Kalman.html#2dd268f2d7fbe6382cb8825a1114192a" title="cache of fy.R">_Ry</a> +=<a class="code" href="classbdm_1_1Kalman.html#475b088287cdfbba4dc60a3d027728b7" title="Matrix R in square-root form.">R</a>;
314	<a name="l00371"></a>00371
315	<a name="l00372"></a>00372 mat Pfull = <a class="code" href="classbdm_1_1Kalman.html#00c27b0bf324f0018497921ca23c71ed" title="cache of est.R">_P</a>.to_mat();
316	<a name="l00373"></a>00373
317	<a name="l00374"></a>00374 <a class="code" href="classbdm_1_1Kalman.html#2dd268f2d7fbe6382cb8825a1114192a" title="cache of fy.R">_Ry</a>.inv ( iRy ); <span class="comment">// result is in _iRy;</span>
318	<a name="l00375"></a>00375 <a class="code" href="classbdm_1_1Kalman.html#bd69dfb802465f22dd84d73a180d5c92" title="placeholder for Kalman gain">_K</a> = Pfull<a class="code" href="classbdm_1_1Kalman.html#818eba63a23972786a4579ad30294177" title="Matrix C.">C</a>.transpose() ( iRy.to_mat() );
319	<a name="l00376"></a>00376
320	<a name="l00377"></a>00377 sq_T pom ( ( <span class="keywordtype">int</span> ) Pfull.rows() );
321	<a name="l00378"></a>00378 iRy.mult_sym_t ( <a class="code" href="classbdm_1_1Kalman.html#818eba63a23972786a4579ad30294177" title="Matrix C.">C</a>*Pfull,pom );
322	<a name="l00379"></a>00379 ( <a class="code" href="classbdm_1_1Kalman.html#00c27b0bf324f0018497921ca23c71ed" title="cache of est.R">_P</a> ) -= pom; <span class="comment">// P = P -PC'iRy*CP;</span>
323	<a name="l00380"></a>00380 ( <a class="code" href="classbdm_1_1Kalman.html#c249d45258c8578b13858ad3e7b729b1" title="cache of fy.mu">_yp</a> ) = <a class="code" href="classbdm_1_1Kalman.html#818eba63a23972786a4579ad30294177" title="Matrix C.">C</a>* <a class="code" href="classbdm_1_1Kalman.html#fa172078091e45561343fa513dd573b0" title="cache of est.mu">_mu</a> +<a class="code" href="classbdm_1_1Kalman.html#7b56ac423d0654b5755e4f852a870456" title="Matrix D.">D</a>*u; <span class="comment">//y prediction</span>
324	<a name="l00381"></a>00381 ( <a class="code" href="classbdm_1_1Kalman.html#fa172078091e45561343fa513dd573b0" title="cache of est.mu">_mu</a> ) += <a class="code" href="classbdm_1_1Kalman.html#bd69dfb802465f22dd84d73a180d5c92" title="placeholder for Kalman gain">_K</a>* ( y- <a class="code" href="classbdm_1_1Kalman.html#c249d45258c8578b13858ad3e7b729b1" title="cache of fy.mu">_yp</a> );
325	<a name="l00382"></a>00382
326	<a name="l00383"></a>00383
327	<a name="l00384"></a>00384 <span class="keywordflow">if</span> ( <a class="code" href="classbdm_1_1BM.html#faff0ad12556fe7dc0e2807d4fd938ee" title="If true, the filter will compute likelihood of the data record and store it in ll...">evalll</a>==<span class="keyword">true</span> ) <span class="comment">//likelihood of observation y</span>
328	<a name="l00385"></a>00385 {
329	<a name="l00386"></a>00386 <a class="code" href="classbdm_1_1BM.html#4064b6559d962633e4372b12f4cd204a" title="Logarithm of marginalized data likelihood.">ll</a>=<a class="code" href="classbdm_1_1Kalman.html#ba555c394c429f6831c9bbabfa2c944c" title="preditive density on $y_t$">fy</a>.evallog ( y );
330	<a name="l00387"></a>00387 }
331	<a name="l00388"></a>00388
332	<a name="l00389"></a>00389 <span class="comment">//cout << "y: " << y-(*_yp) <<" R: " << _Ry->to_mat() << " iR: " << _iRy->to_mat() << " ll: " << ll <<endl;</span>
333	<a name="l00390"></a>00390
334	<a name="l00391"></a>00391 };
335	<a name="l00392"></a>00392
336	<a name="l00400"></a><a class="code" href="classbdm_1_1MultiModel.html">00400</a> <span class="keyword">class </span><a class="code" href="classbdm_1_1MultiModel.html" title="(Switching) Multiple Model The model runs several models in parallel and evaluates...">MultiModel</a>: <span class="keyword">public</span> <a class="code" href="classbdm_1_1BM.html" title="Bayesian Model of a system, i.e. all uncertainty is modeled by probabilities.">BM</a>
337	<a name="l00401"></a>00401 {
338	<a name="l00402"></a>00402 <span class="keyword">protected</span>:
339	<a name="l00404"></a><a class="code" href="classbdm_1_1MultiModel.html#33de5d07ee774070632de8963b5d4c93">00404</a> Array<EKFCh*> <a class="code" href="classbdm_1_1MultiModel.html#33de5d07ee774070632de8963b5d4c93" title="List of models between which we switch.">Models</a>;
340	<a name="l00406"></a><a class="code" href="classbdm_1_1MultiModel.html#ef85ea61575bffa8beac8040869ee47a">00406</a> vec <a class="code" href="classbdm_1_1MultiModel.html#ef85ea61575bffa8beac8040869ee47a" title="vector of model weights">w</a>;
341	<a name="l00408"></a><a class="code" href="classbdm_1_1MultiModel.html#7b4012fc2208ce4ddd5c0d1fe69d7634">00408</a> vec <a class="code" href="classbdm_1_1MultiModel.html#7b4012fc2208ce4ddd5c0d1fe69d7634" title="cache of model lls">_lls</a>;
342	<a name="l00410"></a><a class="code" href="classbdm_1_1MultiModel.html#9b56bcde4664bd53f8995d7ee7ed415c">00410</a> <span class="keywordtype">int</span> <a class="code" href="classbdm_1_1MultiModel.html#9b56bcde4664bd53f8995d7ee7ed415c" title="type of switching policy [1=maximum,2=...]">policy</a>;
343	<a name="l00412"></a><a class="code" href="classbdm_1_1MultiModel.html#d665551d045b1a1055eeb9185558ff0b">00412</a> <a class="code" href="classbdm_1_1enorm.html">enorm<chmat></a> <a class="code" href="classbdm_1_1MultiModel.html#d665551d045b1a1055eeb9185558ff0b" title="internal statistics">est</a>;
344	<a name="l00413"></a>00413 <span class="keyword">public</span>:
345	<a name="l00414"></a>00414 <span class="keywordtype">void</span> set_parameters ( Array<EKFCh*> A, <span class="keywordtype">int</span> pol0=1 )
346	<a name="l00415"></a>00415 {
347	<a name="l00416"></a>00416 <a class="code" href="classbdm_1_1MultiModel.html#33de5d07ee774070632de8963b5d4c93" title="List of models between which we switch.">Models</a>=A;<span class="comment">//TODO: test if evalll is set</span>
348	<a name="l00417"></a>00417 <a class="code" href="classbdm_1_1MultiModel.html#ef85ea61575bffa8beac8040869ee47a" title="vector of model weights">w</a>.set_length ( A.length() );
349	<a name="l00418"></a>00418 <a class="code" href="classbdm_1_1MultiModel.html#7b4012fc2208ce4ddd5c0d1fe69d7634" title="cache of model lls">_lls</a>.set_length ( A.length() );
350	<a name="l00419"></a>00419 <a class="code" href="classbdm_1_1MultiModel.html#9b56bcde4664bd53f8995d7ee7ed415c" title="type of switching policy [1=maximum,2=...]">policy</a>=pol0;
351	<a name="l00420"></a>00420
352	<a name="l00421"></a>00421 <a class="code" href="classbdm_1_1MultiModel.html#d665551d045b1a1055eeb9185558ff0b" title="internal statistics">est</a>.<a class="code" href="classbdm_1_1epdf.html#f423e28448dbb69ef4905295ec8de8ff" title="Name its rv.">set_rv</a>(<a class="code" href="classbdm_1_1RV.html" title="Class representing variables, most often random variables.">RV</a>(<span class="stringliteral">"MM"</span>,A(0)->posterior().dimension(),0));
353	<a name="l00422"></a>00422 <a class="code" href="classbdm_1_1MultiModel.html#d665551d045b1a1055eeb9185558ff0b" title="internal statistics">est</a>.<a class="code" href="classbdm_1_1enorm.html#b8322f2c11560871dd922c660f4771bb">set_parameters</a>(A(0)->_e()->mean(), A(0)->_e()->_R());
354	<a name="l00423"></a>00423 }
355	<a name="l00424"></a><a class="code" href="classbdm_1_1MultiModel.html#a915deeddb0e94c337d02ebc0abe535e">00424</a> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1MultiModel.html#a915deeddb0e94c337d02ebc0abe535e" title="Incremental Bayes rule.">bayes</a> ( <span class="keyword">const</span> vec &dt )
356	<a name="l00425"></a>00425 {
357	<a name="l00426"></a>00426 <span class="keywordtype">int</span> n = <a class="code" href="classbdm_1_1MultiModel.html#33de5d07ee774070632de8963b5d4c93" title="List of models between which we switch.">Models</a>.length();
358	<a name="l00427"></a>00427 <span class="keywordtype">int</span> i;
359	<a name="l00428"></a>00428 <span class="keywordflow">for</span> ( i=0;i<n;i++ )
360	<a name="l00429"></a>00429 {
361	<a name="l00430"></a>00430 <a class="code" href="classbdm_1_1MultiModel.html#33de5d07ee774070632de8963b5d4c93" title="List of models between which we switch.">Models</a> ( i )->bayes ( dt );
362	<a name="l00431"></a>00431 <a class="code" href="classbdm_1_1MultiModel.html#7b4012fc2208ce4ddd5c0d1fe69d7634" title="cache of model lls">_lls</a> ( i ) = <a class="code" href="classbdm_1_1MultiModel.html#33de5d07ee774070632de8963b5d4c93" title="List of models between which we switch.">Models</a> ( i )->_ll();
363	<a name="l00432"></a>00432 }
364	<a name="l00433"></a>00433 <span class="keywordtype">double</span> mlls=max ( <a class="code" href="classbdm_1_1MultiModel.html#7b4012fc2208ce4ddd5c0d1fe69d7634" title="cache of model lls">_lls</a> );
365	<a name="l00434"></a>00434 <a class="code" href="classbdm_1_1MultiModel.html#ef85ea61575bffa8beac8040869ee47a" title="vector of model weights">w</a>=exp ( <a class="code" href="classbdm_1_1MultiModel.html#7b4012fc2208ce4ddd5c0d1fe69d7634" title="cache of model lls">_lls</a>-mlls );
366	<a name="l00435"></a>00435 <a class="code" href="classbdm_1_1MultiModel.html#ef85ea61575bffa8beac8040869ee47a" title="vector of model weights">w</a>/=sum ( <a class="code" href="classbdm_1_1MultiModel.html#ef85ea61575bffa8beac8040869ee47a" title="vector of model weights">w</a> ); <span class="comment">//normalization</span>
367	<a name="l00436"></a>00436 <span class="comment">//set statistics</span>
368	<a name="l00437"></a>00437 <span class="keywordflow">switch</span> ( <a class="code" href="classbdm_1_1MultiModel.html#9b56bcde4664bd53f8995d7ee7ed415c" title="type of switching policy [1=maximum,2=...]">policy</a> )
369	<a name="l00438"></a>00438 {
370	<a name="l00439"></a>00439 <span class="keywordflow">case</span> 1:
371	<a name="l00440"></a>00440 {
372	<a name="l00441"></a>00441 <span class="keywordtype">int</span> mi=max_index ( <a class="code" href="classbdm_1_1MultiModel.html#ef85ea61575bffa8beac8040869ee47a" title="vector of model weights">w</a> );
373	<a name="l00442"></a>00442 <span class="keyword">const</span> <a class="code" href="classbdm_1_1enorm.html">enorm<chmat></a>* st=(<a class="code" href="classbdm_1_1MultiModel.html#33de5d07ee774070632de8963b5d4c93" title="List of models between which we switch.">Models</a>(mi)->_e());
374	<a name="l00443"></a>00443 <a class="code" href="classbdm_1_1MultiModel.html#d665551d045b1a1055eeb9185558ff0b" title="internal statistics">est</a>.<a class="code" href="classbdm_1_1enorm.html#b8322f2c11560871dd922c660f4771bb">set_parameters</a>(st-><a class="code" href="classbdm_1_1enorm.html#b2fa2915c35366392fe9bb022ca1a600" title="return expected value">mean</a>(), st-><a class="code" href="classbdm_1_1enorm.html#81d81e35e57c9f194bde248e3affcf1f">_R</a>());
375	<a name="l00444"></a>00444 }
376	<a name="l00445"></a>00445 <span class="keywordflow">break</span>;
377	<a name="l00446"></a>00446 <span class="keywordflow">default</span>: it_error ( <span class="stringliteral">"unknown policy"</span> );
378	<a name="l00447"></a>00447 }
379	<a name="l00448"></a>00448 <span class="comment">// copy result to all models</span>
380	<a name="l00449"></a>00449 <span class="keywordflow">for</span> ( i=0;i<n;i++ )
381	<a name="l00450"></a>00450 {
382	<a name="l00451"></a>00451 <a class="code" href="classbdm_1_1MultiModel.html#33de5d07ee774070632de8963b5d4c93" title="List of models between which we switch.">Models</a> ( i )->set_statistics ( <a class="code" href="classbdm_1_1MultiModel.html#d665551d045b1a1055eeb9185558ff0b" title="internal statistics">est</a>.<a class="code" href="classbdm_1_1enorm.html#b2fa2915c35366392fe9bb022ca1a600" title="return expected value">mean</a>(),<a class="code" href="classbdm_1_1MultiModel.html#d665551d045b1a1055eeb9185558ff0b" title="internal statistics">est</a>.<a class="code" href="classbdm_1_1enorm.html#81d81e35e57c9f194bde248e3affcf1f">_R</a>());
383	<a name="l00452"></a>00452 }
384	<a name="l00453"></a>00453 }
385	<a name="l00454"></a>00454 <span class="comment">//all posterior densities are equal => return the first one</span>
386	<a name="l00455"></a>00455 <span class="keyword">const</span> <a class="code" href="classbdm_1_1enorm.html">enorm<chmat></a>* _e()<span class="keyword"> const </span>{<span class="keywordflow">return</span> &<a class="code" href="classbdm_1_1MultiModel.html#d665551d045b1a1055eeb9185558ff0b" title="internal statistics">est</a>;}
387	<a name="l00456"></a>00456 <span class="comment">//all posterior densities are equal => return the first one</span>
388	<a name="l00457"></a>00457 <span class="keyword">const</span> enorm<chmat>& posterior()<span class="keyword"> const </span>{<span class="keywordflow">return</span> <a class="code" href="classbdm_1_1MultiModel.html#d665551d045b1a1055eeb9185558ff0b" title="internal statistics">est</a>;}
389	<a name="l00458"></a>00458
390	<a name="l00459"></a>00459 <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1MultiModel.html#2357434d2ec3c9b4e44e962bdfceda4e" title="This method arrange instance properties according the data stored in the Setting...">from_setting</a>( <span class="keyword">const</span> Setting &root );
391	<a name="l00460"></a>00460
392	<a name="l00461"></a>00461 <span class="comment">// TODO dodelat void to_setting( Setting &root ) const;</span>
393	<a name="l00462"></a>00462
394	<a name="l00463"></a>00463 };
395	<a name="l00464"></a>00464
396	<a name="l00465"></a>00465 UIREGISTER(MultiModel);
397	<a name="l00466"></a>00466
398	<a name="l00467"></a>00467
399	<a name="l00468"></a>00468
400	<a name="l00469"></a>00469 <span class="comment">//TODO why not const pointer??</span>
401	<a name="l00470"></a>00470
402	<a name="l00471"></a>00471 <span class="keyword">template</span><<span class="keyword">class</span> sq_T>
403	<a name="l00472"></a><a class="code" href="classbdm_1_1EKF.html#d087a8bb408d26ac4f5c542746b81059">00472</a> <a class="code" href="classbdm_1_1EKF.html#d087a8bb408d26ac4f5c542746b81059" title="Default constructor.">EKF<sq_T>::EKF</a> ( <a class="code" href="classbdm_1_1RV.html" title="Class representing variables, most often random variables.">RV</a> rvx0, <a class="code" href="classbdm_1_1RV.html" title="Class representing variables, most often random variables.">RV</a> rvy0, <a class="code" href="classbdm_1_1RV.html" title="Class representing variables, most often random variables.">RV</a> rvu0 ) : <a class="code" href="classbdm_1_1Kalman.html" title="Kalman filter with covariance matrices in square root form.">Kalman</a><sq_T> ( rvx0,rvy0,rvu0 ) {}
404	<a name="l00473"></a>00473
405	<a name="l00474"></a>00474 <span class="keyword">template</span><<span class="keyword">class</span> sq_T>
406	<a name="l00475"></a><a class="code" href="classbdm_1_1EKF.html#00fec1a0a6a467eb83fb36c65eba7bcb">00475</a> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1EKF.html#00fec1a0a6a467eb83fb36c65eba7bcb" title="Set nonlinear functions for mean values and covariance matrices.">EKF<sq_T>::set_parameters</a> ( <a class="code" href="classbdm_1_1diffbifn.html" title="Class representing a differentiable function of two variables .">diffbifn</a>* pfxu0, <a class="code" href="classbdm_1_1diffbifn.html" title="Class representing a differentiable function of two variables .">diffbifn</a>* phxu0,<span class="keyword">const</span> sq_T Q0,<span class="keyword">const</span> sq_T R0 )
407	<a name="l00476"></a>00476 {
408	<a name="l00477"></a>00477 pfxu = pfxu0;
409	<a name="l00478"></a>00478 phxu = phxu0;
410	<a name="l00479"></a>00479
411	<a name="l00480"></a>00480 <span class="comment">//initialize matrices A C, later, these will be only updated!</span>
412	<a name="l00481"></a>00481 pfxu-><a class="code" href="classbdm_1_1diffbifn.html#651184f808a35f236dbfea21aca1b6ac" title="Evaluates and writes result into A .">dfdx_cond</a> ( <a class="code" href="classbdm_1_1Kalman.html#fa172078091e45561343fa513dd573b0" title="cache of est.mu">_mu</a>,zeros ( <a class="code" href="classbdm_1_1Kalman.html#c5136ef617f6ac0e426bea222755d92b" title="cache of rvu.count()">dimu</a> ),<a class="code" href="classbdm_1_1Kalman.html#0a2072e2090c10fac74ad30a023a4ace" title="Matrix A.">A</a>,<span class="keyword">true</span> );
413	<a name="l00482"></a>00482 <span class="comment">// pfxu->dfdu_cond ( *_mu,zeros ( dimu ),B,true );</span>
414	<a name="l00483"></a>00483 <a class="code" href="classbdm_1_1Kalman.html#5977b2c81857948a35105f0e7840203c" title="Matrix B.">B</a>.clear();
415	<a name="l00484"></a>00484 phxu-><a class="code" href="classbdm_1_1diffbifn.html#651184f808a35f236dbfea21aca1b6ac" title="Evaluates and writes result into A .">dfdx_cond</a> ( <a class="code" href="classbdm_1_1Kalman.html#fa172078091e45561343fa513dd573b0" title="cache of est.mu">_mu</a>,zeros ( <a class="code" href="classbdm_1_1Kalman.html#c5136ef617f6ac0e426bea222755d92b" title="cache of rvu.count()">dimu</a> ),<a class="code" href="classbdm_1_1Kalman.html#818eba63a23972786a4579ad30294177" title="Matrix C.">C</a>,<span class="keyword">true</span> );
416	<a name="l00485"></a>00485 <span class="comment">// phxu->dfdu_cond ( *_mu,zeros ( dimu ),D,true );</span>
417	<a name="l00486"></a>00486 <a class="code" href="classbdm_1_1Kalman.html#7b56ac423d0654b5755e4f852a870456" title="Matrix D.">D</a>.clear();
418	<a name="l00487"></a>00487
419	<a name="l00488"></a>00488 <a class="code" href="classbdm_1_1Kalman.html#475b088287cdfbba4dc60a3d027728b7" title="Matrix R in square-root form.">R</a> = R0;
420	<a name="l00489"></a>00489 <a class="code" href="classbdm_1_1Kalman.html#70f8bf19e81b532c60fd3a7a152425ee" title="Matrix Q in square-root form.">Q</a> = Q0;
421	<a name="l00490"></a>00490 }
422	<a name="l00491"></a>00491
423	<a name="l00492"></a>00492 <span class="keyword">template</span><<span class="keyword">class</span> sq_T>
424	<a name="l00493"></a><a class="code" href="classbdm_1_1EKF.html#3fb182ecc29b10ca1163cecbf3bcccfa">00493</a> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1EKF.html#3fb182ecc29b10ca1163cecbf3bcccfa" title="Here dt = [yt;ut] of appropriate dimensions.">EKF<sq_T>::bayes</a> ( <span class="keyword">const</span> vec &dt )
425	<a name="l00494"></a>00494 {
426	<a name="l00495"></a>00495 it_assert_debug ( dt.length() == ( <a class="code" href="classbdm_1_1Kalman.html#d2c36ba01760bf207b985bf321b7817f" title="cache of rvy.count()">dimy</a>+<a class="code" href="classbdm_1_1Kalman.html#c5136ef617f6ac0e426bea222755d92b" title="cache of rvu.count()">dimu</a> ),<span class="stringliteral">"KalmanFull::bayes wrong size of dt"</span> );
427	<a name="l00496"></a>00496
428	<a name="l00497"></a>00497 sq_T iRy ( <a class="code" href="classbdm_1_1Kalman.html#d2c36ba01760bf207b985bf321b7817f" title="cache of rvy.count()">dimy</a>,<a class="code" href="classbdm_1_1Kalman.html#d2c36ba01760bf207b985bf321b7817f" title="cache of rvy.count()">dimy</a> );
429	<a name="l00498"></a>00498 vec u = dt.get ( <a class="code" href="classbdm_1_1Kalman.html#d2c36ba01760bf207b985bf321b7817f" title="cache of rvy.count()">dimy</a>,<a class="code" href="classbdm_1_1Kalman.html#d2c36ba01760bf207b985bf321b7817f" title="cache of rvy.count()">dimy</a>+<a class="code" href="classbdm_1_1Kalman.html#c5136ef617f6ac0e426bea222755d92b" title="cache of rvu.count()">dimu</a>-1 );
430	<a name="l00499"></a>00499 vec y = dt.get ( 0,<a class="code" href="classbdm_1_1Kalman.html#d2c36ba01760bf207b985bf321b7817f" title="cache of rvy.count()">dimy</a>-1 );
431	<a name="l00500"></a>00500 <span class="comment">//Time update</span>
432	<a name="l00501"></a>00501 <a class="code" href="classbdm_1_1Kalman.html#fa172078091e45561343fa513dd573b0" title="cache of est.mu">_mu</a> = pfxu-><a class="code" href="classbdm_1_1diffbifn.html#188f31066bd72e1bf0ddacd1eb0e6af3" title="Evaluates (VS: Do we really need common eval? ).">eval</a> ( <a class="code" href="classbdm_1_1Kalman.html#fa172078091e45561343fa513dd573b0" title="cache of est.mu">_mu</a>, u );
433	<a name="l00502"></a>00502 pfxu-><a class="code" href="classbdm_1_1diffbifn.html#651184f808a35f236dbfea21aca1b6ac" title="Evaluates and writes result into A .">dfdx_cond</a> ( <a class="code" href="classbdm_1_1Kalman.html#fa172078091e45561343fa513dd573b0" title="cache of est.mu">_mu</a>,u,<a class="code" href="classbdm_1_1Kalman.html#0a2072e2090c10fac74ad30a023a4ace" title="Matrix A.">A</a>,<span class="keyword">false</span> ); <span class="comment">//update A by a derivative of fx</span>
434	<a name="l00503"></a>00503
435	<a name="l00504"></a>00504 <span class="comment">//P = APA.transpose() + Q; in sq_T</span>
436	<a name="l00505"></a>00505 <a class="code" href="classbdm_1_1Kalman.html#00c27b0bf324f0018497921ca23c71ed" title="cache of est.R">_P</a>.<a class="code" href="classfsqmat.html#5530d2756b5d991de755e6121c9a452e" title="Inplace symmetric multiplication by a SQUARE matrix , i.e. .">mult_sym</a> ( <a class="code" href="classbdm_1_1Kalman.html#0a2072e2090c10fac74ad30a023a4ace" title="Matrix A.">A</a> );
437	<a name="l00506"></a>00506 <a class="code" href="classbdm_1_1Kalman.html#00c27b0bf324f0018497921ca23c71ed" title="cache of est.R">_P</a> +=<a class="code" href="classbdm_1_1Kalman.html#70f8bf19e81b532c60fd3a7a152425ee" title="Matrix Q in square-root form.">Q</a>;
438	<a name="l00507"></a>00507
439	<a name="l00508"></a>00508 <span class="comment">//Data update</span>
440	<a name="l00509"></a>00509 phxu-><a class="code" href="classbdm_1_1diffbifn.html#651184f808a35f236dbfea21aca1b6ac" title="Evaluates and writes result into A .">dfdx_cond</a> ( <a class="code" href="classbdm_1_1Kalman.html#fa172078091e45561343fa513dd573b0" title="cache of est.mu">_mu</a>,u,<a class="code" href="classbdm_1_1Kalman.html#818eba63a23972786a4579ad30294177" title="Matrix C.">C</a>,<span class="keyword">false</span> ); <span class="comment">//update C by a derivative hx</span>
441	<a name="l00510"></a>00510 <span class="comment">//_Ry = CPC.transpose() + R; in sq_T</span>
442	<a name="l00511"></a>00511 <a class="code" href="classbdm_1_1Kalman.html#00c27b0bf324f0018497921ca23c71ed" title="cache of est.R">_P</a>.<a class="code" href="classfsqmat.html#5530d2756b5d991de755e6121c9a452e" title="Inplace symmetric multiplication by a SQUARE matrix , i.e. .">mult_sym</a> ( <a class="code" href="classbdm_1_1Kalman.html#818eba63a23972786a4579ad30294177" title="Matrix C.">C</a>, <a class="code" href="classbdm_1_1Kalman.html#2dd268f2d7fbe6382cb8825a1114192a" title="cache of fy.R">_Ry</a> );
443	<a name="l00512"></a>00512 ( <a class="code" href="classbdm_1_1Kalman.html#2dd268f2d7fbe6382cb8825a1114192a" title="cache of fy.R">_Ry</a> ) +=<a class="code" href="classbdm_1_1Kalman.html#475b088287cdfbba4dc60a3d027728b7" title="Matrix R in square-root form.">R</a>;
444	<a name="l00513"></a>00513
445	<a name="l00514"></a>00514 mat Pfull = <a class="code" href="classbdm_1_1Kalman.html#00c27b0bf324f0018497921ca23c71ed" title="cache of est.R">_P</a>.<a class="code" href="classfsqmat.html#f54fc955e8e3b43d15afa92124bc24b3" title="Conversion to full matrix.">to_mat</a>();
446	<a name="l00515"></a>00515
447	<a name="l00516"></a>00516 <a class="code" href="classbdm_1_1Kalman.html#2dd268f2d7fbe6382cb8825a1114192a" title="cache of fy.R">_Ry</a>.<a class="code" href="classfsqmat.html#9fa853e1ca28f2a1a1c43377e798ecb1" title="Matrix inversion preserving the chosen form.">inv</a> ( iRy ); <span class="comment">// result is in _iRy;</span>
448	<a name="l00517"></a>00517 <a class="code" href="classbdm_1_1Kalman.html#bd69dfb802465f22dd84d73a180d5c92" title="placeholder for Kalman gain">_K</a> = Pfull<a class="code" href="classbdm_1_1Kalman.html#818eba63a23972786a4579ad30294177" title="Matrix C.">C</a>.transpose() ( iRy.to_mat() );
449	<a name="l00518"></a>00518
450	<a name="l00519"></a>00519 sq_T pom ( ( <span class="keywordtype">int</span> ) Pfull.rows() );
451	<a name="l00520"></a>00520 iRy.mult_sym_t ( <a class="code" href="classbdm_1_1Kalman.html#818eba63a23972786a4579ad30294177" title="Matrix C.">C</a>*Pfull,pom );
452	<a name="l00521"></a>00521 ( <a class="code" href="classbdm_1_1Kalman.html#00c27b0bf324f0018497921ca23c71ed" title="cache of est.R">_P</a> ) -= pom; <span class="comment">// P = P -PC'iRy*CP;</span>
453	<a name="l00522"></a>00522 <a class="code" href="classbdm_1_1Kalman.html#c249d45258c8578b13858ad3e7b729b1" title="cache of fy.mu">_yp</a> = phxu-><a class="code" href="classbdm_1_1diffbifn.html#188f31066bd72e1bf0ddacd1eb0e6af3" title="Evaluates (VS: Do we really need common eval? ).">eval</a> ( <a class="code" href="classbdm_1_1Kalman.html#fa172078091e45561343fa513dd573b0" title="cache of est.mu">_mu</a>,u ); <span class="comment">//y prediction</span>
454	<a name="l00523"></a>00523 ( <a class="code" href="classbdm_1_1Kalman.html#fa172078091e45561343fa513dd573b0" title="cache of est.mu">_mu</a> ) += <a class="code" href="classbdm_1_1Kalman.html#bd69dfb802465f22dd84d73a180d5c92" title="placeholder for Kalman gain">_K</a>* ( y-<a class="code" href="classbdm_1_1Kalman.html#c249d45258c8578b13858ad3e7b729b1" title="cache of fy.mu">_yp</a> );
455	<a name="l00524"></a>00524
456	<a name="l00525"></a>00525 <span class="keywordflow">if</span> ( <a class="code" href="classbdm_1_1BM.html#faff0ad12556fe7dc0e2807d4fd938ee" title="If true, the filter will compute likelihood of the data record and store it in ll...">evalll</a>==<span class="keyword">true</span> ) {<a class="code" href="classbdm_1_1BM.html#4064b6559d962633e4372b12f4cd204a" title="Logarithm of marginalized data likelihood.">ll</a>+=<a class="code" href="classbdm_1_1Kalman.html#ba555c394c429f6831c9bbabfa2c944c" title="preditive density on $y_t$">fy</a>.<a class="code" href="classbdm_1_1eEF.html#a36d06ecdd6f4c79dc122510eaccc692" title="Evaluate normalized log-probability.">evallog</a> ( y );}
457	<a name="l00526"></a>00526 };
458	<a name="l00527"></a>00527
459	<a name="l00528"></a>00528
460	<a name="l00529"></a>00529 }
461	<a name="l00530"></a>00530 <span class="preprocessor">#endif // KF_H</span>
462	<a name="l00531"></a>00531 <span class="preprocessor"></span>
463	<a name="l00532"></a>00532
464	</pre></div></div>
465	<hr size="1"><address style="text-align: right;"><small>Generated on Wed Jun 17 14:13:28 2009 for mixpp by
466	<a href="http://www.doxygen.org/index.html">
467	<img src="doxygen.png" alt="doxygen" align="middle" border="0"></a> 1.5.8 </small></address>
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