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3<title>mixpp: KalmanFull Class Reference</title>
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7<!-- Generated by Doxygen 1.5.3 -->
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9  <ul>
10    <li><a href="index.html"><span>Main&nbsp;Page</span></a></li>
11    <li class="current"><a href="annotated.html"><span>Classes</span></a></li>
12    <li><a href="files.html"><span>Files</span></a></li>
13    <li><a href="pages.html"><span>Related&nbsp;Pages</span></a></li>
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17  <ul>
18    <li><a href="annotated.html"><span>Class&nbsp;List</span></a></li>
19    <li><a href="hierarchy.html"><span>Class&nbsp;Hierarchy</span></a></li>
20    <li><a href="functions.html"><span>Class&nbsp;Members</span></a></li>
21  </ul>
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23<h1>KalmanFull Class Reference</h1><!-- doxytag: class="KalmanFull" --><!-- doxytag: inherits="BM" -->Basic <a class="el" href="classKalman.html" title="Kalman filter with covariance matrices in square root form.">Kalman</a> filter with full matrices (education purpose only)! Will be deleted soon! 
24<a href="#_details">More...</a>
25<p>
26<code>#include &lt;<a class="el" href="libKF_8h-source.html">libKF.h</a>&gt;</code>
27<p>
28<div class="dynheader">
29Inheritance diagram for KalmanFull:</div>
30<div class="dynsection">
31<p><center><img src="classKalmanFull__inherit__graph.png" border="0" usemap="#KalmanFull__inherit__map" alt="Inheritance graph"></center>
32<map name="KalmanFull__inherit__map">
33<area shape="rect" href="classBM.html" title="Bayesian Model of the world, i.e. all uncertainty is modeled by probabilities." alt="" coords="29,7,72,33"></map>
34<center><font size="2">[<a href="graph_legend.html">legend</a>]</font></center></div>
35<div class="dynheader">
36Collaboration diagram for KalmanFull:</div>
37<div class="dynsection">
38<p><center><img src="classKalmanFull__coll__graph.png" border="0" usemap="#KalmanFull__coll__map" alt="Collaboration graph"></center>
39<map name="KalmanFull__coll__map">
40<area shape="rect" href="classBM.html" title="Bayesian Model of the world, i.e. all uncertainty is modeled by probabilities." alt="" coords="29,7,72,33"></map>
41<center><font size="2">[<a href="graph_legend.html">legend</a>]</font></center></div>
42
43<p>
44<a href="classKalmanFull-members.html">List of all members.</a><table border="0" cellpadding="0" cellspacing="0">
45<tr><td></td></tr>
46<tr><td colspan="2"><br><h2>Public Member Functions</h2></td></tr>
47<tr><td class="memItemLeft" nowrap align="right" valign="top"><a class="anchor" name="7197ab6e7380790006394eabd3b97043"></a><!-- doxytag: member="KalmanFull::KalmanFull" ref="7197ab6e7380790006394eabd3b97043" args="(mat A, mat B, mat C, mat D, mat R, mat Q, mat P0, vec mu0)" -->
48&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classKalmanFull.html#7197ab6e7380790006394eabd3b97043">KalmanFull</a> (mat A, mat B, mat C, mat D, mat R, mat Q, mat P0, vec mu0)</td></tr>
49
50<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Full constructor. <br></td></tr>
51<tr><td class="memItemLeft" nowrap align="right" valign="top"><a class="anchor" name="048b13739b94c331cda08249b278552b"></a><!-- doxytag: member="KalmanFull::bayes" ref="048b13739b94c331cda08249b278552b" args="(const vec &amp;dt, bool evalll=true)" -->
52void&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classKalmanFull.html#048b13739b94c331cda08249b278552b">bayes</a> (const vec &amp;dt, bool <a class="el" href="classBM.html#bf6fb59b30141074f8ee1e2f43d03129">evalll</a>=true)</td></tr>
53
54<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Here dt = [yt;ut] of appropriate dimensions. <br></td></tr>
55<tr><td class="memItemLeft" nowrap align="right" valign="top">virtual void&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classBM.html#a892eff438aab2dd1a9e2efcb7fb5bdf">bayes</a> (const vec &amp;dt)=0</td></tr>
56
57<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Incremental Bayes rule.  <a href="#a892eff438aab2dd1a9e2efcb7fb5bdf"></a><br></td></tr>
58<tr><td class="memItemLeft" nowrap align="right" valign="top"><a class="anchor" name="87b07867fd4c133aa89a18543f68d9f9"></a><!-- doxytag: member="KalmanFull::bayes" ref="87b07867fd4c133aa89a18543f68d9f9" args="(mat Dt)" -->
59void&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classBM.html#87b07867fd4c133aa89a18543f68d9f9">bayes</a> (mat Dt)</td></tr>
60
61<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Batch Bayes rule (columns of Dt are observations). <br></td></tr>
62<tr><td class="memItemLeft" nowrap align="right" valign="top"><a class="anchor" name="a5b8f6c8a872738cfaa30ab010e8c077"></a><!-- doxytag: member="KalmanFull::_epdf" ref="a5b8f6c8a872738cfaa30ab010e8c077" args="()" -->
63<a class="el" href="classepdf.html">epdf</a> *&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classBM.html#a5b8f6c8a872738cfaa30ab010e8c077">_epdf</a> ()</td></tr>
64
65<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Returns a pointer to the <a class="el" href="classepdf.html" title="Probability density function with numerical statistics, e.g. posterior density.">epdf</a> representing posterior density on parameters. Use with care! <br></td></tr>
66<tr><td colspan="2"><br><h2>Public Attributes</h2></td></tr>
67<tr><td class="memItemLeft" nowrap align="right" valign="top"><a class="anchor" name="fb5aec635e2720cc5ac31bc01c18a68a"></a><!-- doxytag: member="KalmanFull::mu" ref="fb5aec635e2720cc5ac31bc01c18a68a" args="" -->
68vec&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classKalmanFull.html#fb5aec635e2720cc5ac31bc01c18a68a">mu</a></td></tr>
69
70<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Mean value of the posterior density. <br></td></tr>
71<tr><td class="memItemLeft" nowrap align="right" valign="top"><a class="anchor" name="b75dc059e84fa8ffc076203b30f926cc"></a><!-- doxytag: member="KalmanFull::P" ref="b75dc059e84fa8ffc076203b30f926cc" args="" -->
72mat&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classKalmanFull.html#b75dc059e84fa8ffc076203b30f926cc">P</a></td></tr>
73
74<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Variance of the posterior density. <br></td></tr>
75<tr><td class="memItemLeft" nowrap align="right" valign="top"><a class="anchor" name="5623fef6572a08c2b53b8c87b82dc979"></a><!-- doxytag: member="KalmanFull::ll" ref="5623fef6572a08c2b53b8c87b82dc979" args="" -->
76double&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classBM.html#5623fef6572a08c2b53b8c87b82dc979">ll</a></td></tr>
77
78<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Logarithm of marginalized data likelihood. <br></td></tr>
79<tr><td class="memItemLeft" nowrap align="right" valign="top"><a class="anchor" name="bf6fb59b30141074f8ee1e2f43d03129"></a><!-- doxytag: member="KalmanFull::evalll" ref="bf6fb59b30141074f8ee1e2f43d03129" args="" -->
80bool&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classBM.html#bf6fb59b30141074f8ee1e2f43d03129">evalll</a></td></tr>
81
82<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">If true, the filter will compute likelihood of the data record and store it in <code>ll</code> . Set to false if you want to save time. <br></td></tr>
83<tr><td colspan="2"><br><h2>Friends</h2></td></tr>
84<tr><td class="memItemLeft" nowrap align="right" valign="top"><a class="anchor" name="86ba216243ed95bb46d80d88775d16af"></a><!-- doxytag: member="KalmanFull::operator&lt;&lt;" ref="86ba216243ed95bb46d80d88775d16af" args="(std::ostream &amp;os, const KalmanFull &amp;kf)" -->
85std::ostream &amp;&nbsp;</td><td class="memItemRight" valign="bottom"><b>operator&lt;&lt;</b> (std::ostream &amp;os, const <a class="el" href="classKalmanFull.html">KalmanFull</a> &amp;kf)</td></tr>
86
87</table>
88<hr><a name="_details"></a><h2>Detailed Description</h2>
89Basic <a class="el" href="classKalman.html" title="Kalman filter with covariance matrices in square root form.">Kalman</a> filter with full matrices (education purpose only)! Will be deleted soon! <hr><h2>Member Function Documentation</h2>
90<a class="anchor" name="a892eff438aab2dd1a9e2efcb7fb5bdf"></a><!-- doxytag: member="KalmanFull::bayes" ref="a892eff438aab2dd1a9e2efcb7fb5bdf" args="(const vec &amp;dt)=0" -->
91<div class="memitem">
92<div class="memproto">
93      <table class="memname">
94        <tr>
95          <td class="memname">virtual void BM::bayes           </td>
96          <td>(</td>
97          <td class="paramtype">const vec &amp;&nbsp;</td>
98          <td class="paramname"> <em>dt</em>          </td>
99          <td>&nbsp;)&nbsp;</td>
100          <td width="100%"><code> [pure virtual, inherited]</code></td>
101        </tr>
102      </table>
103</div>
104<div class="memdoc">
105
106<p>
107Incremental Bayes rule.
108<p>
109<dl compact><dt><b>Parameters:</b></dt><dd>
110  <table border="0" cellspacing="2" cellpadding="0">
111    <tr><td valign="top"></td><td valign="top"><em>dt</em>&nbsp;</td><td>vector of input data </td></tr>
112  </table>
113</dl>
114
115</div>
116</div><p>
117<hr>The documentation for this class was generated from the following files:<ul>
118<li>work/mixpp/bdm/estim/<a class="el" href="libKF_8h-source.html">libKF.h</a><li>work/mixpp/bdm/estim/libKF.cpp</ul>
119<hr size="1"><address style="text-align: right;"><small>Generated on Mon Feb 18 21:48:44 2008 for mixpp by&nbsp;
120<a href="http://www.doxygen.org/index.html">
121<img src="doxygen.png" alt="doxygen" align="middle" border="0"></a> 1.5.3 </small></address>
122</body>
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