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[261]21<h1>libKF.h File Reference</h1>Bayesian Filtering for linear Gaussian models (Kalman Filter) and extensions. <a href="#_details">More...</a>
[8]22<p>
[22]23<code>#include &quot;../stat/libFN.h&quot;</code><br>
[32]24<code>#include &quot;<a class="el" href="libEF_8h-source.html">../stat/libEF.h</a>&quot;</code><br>
[37]25<code>#include &quot;<a class="el" href="chmat_8h-source.html">../math/chmat.h</a>&quot;</code><br>
[8]26
27<p>
[19]28<div class="dynheader">
29Include dependency graph for libKF.h:</div>
30<div class="dynsection">
[261]31<p><center><img src="libKF_8h__incl.png" border="0" usemap="#libKF.h_map" alt=""></center>
32<map name="libKF.h_map">
33<area shape="rect" href="libFN_8h-source.html" title="../stat/libFN.h" alt="" coords="5,84,109,111"><area shape="rect" href="libEF_8h.html" title="Probability distributions for Exponential Family models." alt="" coords="133,84,235,111"><area shape="rect" href="chmat_8h.html" title="Matrices in decomposed forms (LDL&#39;, LU, UDU&#39;, etc)." alt="" coords="167,161,289,188"><area shape="rect" href="libBM_8h.html" title="Bayesian Models (bm) that use Bayes rule to learn from observations." alt="" coords="76,161,143,188"><area shape="rect" href="itpp__ext_8h-source.html" title="../itpp_ext.h" alt="" coords="127,316,223,343"><area shape="rect" href="libDC_8h.html" title="Matrices in decomposed forms (LDL&#39;, LU, UDU&#39;, etc)." alt="" coords="183,239,249,265"></map>
[19]34</div>
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[79]37<div class="dynheader">
38This graph shows which files directly or indirectly include this file:</div>
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41<map name="libKF.hdep_map">
42<area shape="rect" href="ekf__templ_8h.html" title="Bayesian Filtering for linear Gaussian models (Kalman Filter) and extensions." alt="" coords="5,84,101,111"></map>
[79]43</div>
44
45<p>
[8]46<a href="libKF_8h-source.html">Go to the source code of this file.</a><table border="0" cellpadding="0" cellspacing="0">
47<tr><td></td></tr>
[255]48<tr><td colspan="2"><br><h2>Namespaces</h2></td></tr>
[261]49<tr><td class="memItemLeft" nowrap align="right" valign="top">namespace &nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacebdm.html">bdm</a></td></tr>
[255]50
[8]51<tr><td colspan="2"><br><h2>Classes</h2></td></tr>
[255]52<tr><td class="memItemLeft" nowrap align="right" valign="top">class &nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classbdm_1_1KalmanFull.html">bdm::KalmanFull</a></td></tr>
[8]53
[255]54<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Basic <a class="el" href="classbdm_1_1Kalman.html" title="Kalman filter with covariance matrices in square root form.">Kalman</a> filter with full matrices (education purpose only)! Will be deleted soon!  <a href="classbdm_1_1KalmanFull.html#_details">More...</a><br></td></tr>
55<tr><td class="memItemLeft" nowrap align="right" valign="top">class &nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classbdm_1_1Kalman.html">bdm::Kalman&lt; sq_T &gt;</a></td></tr>
[8]56
[255]57<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight"><a class="el" href="classbdm_1_1Kalman.html" title="Kalman filter with covariance matrices in square root form.">Kalman</a> filter with covariance matrices in square root form.  <a href="classbdm_1_1Kalman.html#_details">More...</a><br></td></tr>
58<tr><td class="memItemLeft" nowrap align="right" valign="top">class &nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classbdm_1_1KalmanCh.html">bdm::KalmanCh</a></td></tr>
[37]59
[255]60<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight"><a class="el" href="classbdm_1_1Kalman.html" title="Kalman filter with covariance matrices in square root form.">Kalman</a> filter in square root form.  <a href="classbdm_1_1KalmanCh.html#_details">More...</a><br></td></tr>
61<tr><td class="memItemLeft" nowrap align="right" valign="top">class &nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classbdm_1_1EKFfull.html">bdm::EKFfull</a></td></tr>
[79]62
[255]63<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Extended <a class="el" href="classbdm_1_1Kalman.html" title="Kalman filter with covariance matrices in square root form.">Kalman</a> Filter in full matrices.  <a href="classbdm_1_1EKFfull.html#_details">More...</a><br></td></tr>
64<tr><td class="memItemLeft" nowrap align="right" valign="top">class &nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classbdm_1_1EKF.html">bdm::EKF&lt; sq_T &gt;</a></td></tr>
[22]65
[255]66<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Extended <a class="el" href="classbdm_1_1Kalman.html" title="Kalman filter with covariance matrices in square root form.">Kalman</a> Filter.  <a href="classbdm_1_1EKF.html#_details">More...</a><br></td></tr>
67<tr><td class="memItemLeft" nowrap align="right" valign="top">class &nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classbdm_1_1EKFCh.html">bdm::EKFCh</a></td></tr>
[79]68
[255]69<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Extended <a class="el" href="classbdm_1_1Kalman.html" title="Kalman filter with covariance matrices in square root form.">Kalman</a> Filter in Square root.  <a href="classbdm_1_1EKFCh.html#_details">More...</a><br></td></tr>
70<tr><td class="memItemLeft" nowrap align="right" valign="top">class &nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classbdm_1_1KFcondQR.html">bdm::KFcondQR</a></td></tr>
[32]71
[255]72<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight"><a class="el" href="classbdm_1_1Kalman.html" title="Kalman filter with covariance matrices in square root form.">Kalman</a> Filter with conditional diagonal matrices R and Q.  <a href="classbdm_1_1KFcondQR.html#_details">More...</a><br></td></tr>
73<tr><td class="memItemLeft" nowrap align="right" valign="top">class &nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classbdm_1_1KFcondR.html">bdm::KFcondR</a></td></tr>
[33]74
[255]75<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight"><a class="el" href="classbdm_1_1Kalman.html" title="Kalman filter with covariance matrices in square root form.">Kalman</a> Filter with conditional diagonal matrices R and Q.  <a href="classbdm_1_1KFcondR.html#_details">More...</a><br></td></tr>
[8]76</table>
77<hr><a name="_details"></a><h2>Detailed Description</h2>
[255]78Bayesian Filtering for linear Gaussian models (Kalman Filter) and extensions.
[8]79<p>
80<dl class="author" compact><dt><b>Author:</b></dt><dd>Vaclav Smidl.</dd></dl>
81----------------------------------- BDM++ - C++ library for Bayesian Decision Making under Uncertainty<p>
[91]82Using IT++ for numerical operations ----------------------------------- </div>
[264]83<hr size="1"><address style="text-align: right;"><small>Generated on Fri Feb 6 19:49:55 2009 for mixpp by&nbsp;
[8]84<a href="http://www.doxygen.org/index.html">
[139]85<img src="doxygen.png" alt="doxygen" align="middle" border="0"></a> 1.5.6 </small></address>
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