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    r23 r28  
    1111    <li class="current"><a href="annotated.html"><span>Classes</span></a></li> 
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    1314  </ul> 
    1415</div> 
     
    3738<p><center><img src="classEKF__coll__graph.png" border="0" usemap="#EKF_3_01sq__T_01_4__coll__map" alt="Collaboration graph"></center> 
    3839<map name="EKF_3_01sq__T_01_4__coll__map"> 
    39 <area shape="rect" href="classKalman.html" title="Kalman\&lt; fsqmat \&gt;" alt="" coords="61,337,208,364"><area shape="rect" href="classBM.html" title="Bayesian Model of the world, i.e. all uncertainty is modeled by probabilities." alt="" coords="5,7,48,33"><area shape="rect" href="classKalman.html" title="Kalman filter with covariance matrices in square root form." alt="" coords="48,172,176,199"><area shape="rect" href="classfsqmat.html" title="Fake sqmat. This class maps sqmat operations to operations on full matrix." alt="" coords="200,172,267,199"><area shape="rect" title="P\nQ\nR\n_iRy\n_Ry" alt="" coords="229,196,237,204"><area shape="rect" title="P\nQ\nR\n_iRy\n_Ry" alt="" coords="164,333,172,341"><area shape="rect" href="classsqmat.html" title="Virtual class for representation of double symmetric matrices in square&#45;root form..." alt="" coords="203,7,264,33"><area shape="rect" title="\&lt; fsqmat \&gt;" alt="" coords="109,196,117,204"><area shape="rect" title="\&lt; fsqmat \&gt;" alt="" coords="127,333,135,341"><area shape="rect" title="P\nQ\nR\n_iRy\n_Ry" alt="" coords="108,31,116,39"><area shape="rect" title="P\nQ\nR\n_iRy\n_Ry" alt="" coords="108,168,116,176"><area shape="rect" href="classdiffbifn.html" title="Class representing a differentiable function of two variables $f(x,u)$." alt="" coords="277,337,344,364"><area shape="rect" title="fxu\nhxu" alt="" coords="299,361,307,369"><area shape="rect" title="fxu\nhxu" alt="" coords="252,445,260,453"><area shape="rect" href="classfnc.html" title="Class representing function $f(x)$ of variable $x$ represented by rv." alt="" coords="291,172,331,199"><area shape="rect" href="classRV.html" title="Class representing variables, most often random variables." alt="" coords="355,172,392,199"><area shape="rect" title="rvu\nrvx" alt="" coords="365,196,373,204"><area shape="rect" title="rvu\nrvx" alt="" coords="313,333,321,341"></map> 
     40<area shape="rect" href="classKalman.html" title="Kalman\&lt; fsqmat \&gt;" alt="" coords="61,337,208,364"><area shape="rect" href="classBM.html" title="Bayesian Model of the world, i.e. all uncertainty is modeled by probabilities." alt="" coords="5,7,48,33"><area shape="rect" href="classKalman.html" title="Kalman filter with covariance matrices in square root form." alt="" coords="48,172,176,199"><area shape="rect" href="classfsqmat.html" title="Fake sqmat. This class maps sqmat operations to operations on full matrix." alt="" coords="200,172,267,199"><area shape="rect" title="P\nQ\nR\n_iRy\n_Ry" alt="" coords="229,196,237,204"><area shape="rect" title="P\nQ\nR\n_iRy\n_Ry" alt="" coords="164,333,172,341"><area shape="rect" href="classsqmat.html" title="Virtual class for representation of double symmetric matrices in square&#45;root form..." alt="" coords="203,7,264,33"><area shape="rect" title="\&lt; fsqmat \&gt;" alt="" coords="109,196,117,204"><area shape="rect" title="\&lt; fsqmat \&gt;" alt="" coords="127,333,135,341"><area shape="rect" title="P\nQ\nR\n_iRy\n_Ry" alt="" coords="108,31,116,39"><area shape="rect" title="P\nQ\nR\n_iRy\n_Ry" alt="" coords="108,168,116,176"><area shape="rect" href="classdiffbifn.html" title="Class representing a differentiable function of two variables $f(x,u)$." alt="" coords="277,337,344,364"><area shape="rect" title="pfxu\nphxu" alt="" coords="299,361,307,369"><area shape="rect" title="pfxu\nphxu" alt="" coords="252,445,260,453"><area shape="rect" href="classfnc.html" title="Class representing function $f(x)$ of variable $x$ represented by rv." alt="" coords="291,172,331,199"><area shape="rect" href="classRV.html" title="Class representing variables, most often random variables." alt="" coords="355,172,392,199"><area shape="rect" title="rvu\nrvx" alt="" coords="365,196,373,204"><area shape="rect" title="rvu\nrvx" alt="" coords="313,333,321,341"></map> 
    4041<center><font size="2">[<a href="graph_legend.html">legend</a>]</font></center></div> 
    4142 
     
    4445<tr><td></td></tr> 
    4546<tr><td colspan="2"><br><h2>Public Member Functions</h2></td></tr> 
    46 <tr><td class="memItemLeft" nowrap align="right" valign="top"><a class="anchor" name="ec441d41529eeae4a1309426386b4a10"></a><!-- doxytag: member="EKF::EKF" ref="ec441d41529eeae4a1309426386b4a10" args="(const diffbifn fxu, const diffbifn hxu)" --> 
    47 &nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classEKF.html#ec441d41529eeae4a1309426386b4a10">EKF</a> (const <a class="el" href="classdiffbifn.html">diffbifn</a> fxu, const <a class="el" href="classdiffbifn.html">diffbifn</a> hxu)</td></tr> 
     47<tr><td class="memItemLeft" nowrap align="right" valign="top"><a class="anchor" name="003687c6cf2a01be90a00e2c99e3863e"></a><!-- doxytag: member="EKF::EKF" ref="003687c6cf2a01be90a00e2c99e3863e" args="(diffbifn *pfxu, diffbifn *phxu, sq_T Q0, sq_T R0, vec mu0, mat P0)" --> 
     48&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classEKF.html#003687c6cf2a01be90a00e2c99e3863e">EKF</a> (<a class="el" href="classdiffbifn.html">diffbifn</a> *pfxu, <a class="el" href="classdiffbifn.html">diffbifn</a> *phxu, sq_T Q0, sq_T R0, vec mu0, mat P0)</td></tr> 
    4849 
    4950<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Default constructor. <br></td></tr> 
    5051<tr><td class="memItemLeft" nowrap align="right" valign="top"><a class="anchor" name="fb0a08463f14e5584344ea2df99fe747"></a><!-- doxytag: member="EKF::bayes" ref="fb0a08463f14e5584344ea2df99fe747" args="(const vec &amp;dt, bool evalll=true)" --> 
    51 void&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classEKF.html#fb0a08463f14e5584344ea2df99fe747">bayes</a> (const vec &amp;dt, bool evalll=true)</td></tr> 
     52void&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classEKF.html#fb0a08463f14e5584344ea2df99fe747">bayes</a> (const vec &amp;dt, bool <a class="el" href="classBM.html#bf6fb59b30141074f8ee1e2f43d03129">evalll</a>=true)</td></tr> 
    5253 
    5354<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="EKF::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="EKF::_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="3063a3f58a74cea672ae889971012eed"></a><!-- doxytag: member="EKF::mu" ref="3063a3f58a74cea672ae889971012eed" args="" --> 
     68vec&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classKalman.html#3063a3f58a74cea672ae889971012eed">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="188cd5ac1c9e496b1a371eb7c57c97d3"></a><!-- doxytag: member="EKF::P" ref="188cd5ac1c9e496b1a371eb7c57c97d3" args="" --> 
     72<a class="el" href="classfsqmat.html">fsqmat</a>&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classKalman.html#188cd5ac1c9e496b1a371eb7c57c97d3">P</a></td></tr> 
     73 
     74<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Mean value 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="EKF::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="EKF::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>Protected Attributes</h2></td></tr> 
     84<tr><td class="memItemLeft" nowrap align="right" valign="top"><a class="anchor" name="39c8c403b46fa3b8c7da77cb2e3729eb"></a><!-- doxytag: member="EKF::dimx" ref="39c8c403b46fa3b8c7da77cb2e3729eb" args="" --> 
     85int&nbsp;</td><td class="memItemRight" valign="bottom"><b>dimx</b></td></tr> 
     86 
     87<tr><td class="memItemLeft" nowrap align="right" valign="top"><a class="anchor" name="ba17b956df1e38b31fbbc299c8213b6a"></a><!-- doxytag: member="EKF::dimy" ref="ba17b956df1e38b31fbbc299c8213b6a" args="" --> 
     88int&nbsp;</td><td class="memItemRight" valign="bottom"><b>dimy</b></td></tr> 
     89 
     90<tr><td class="memItemLeft" nowrap align="right" valign="top"><a class="anchor" name="b0153795a1444b6968a86409c778d9ce"></a><!-- doxytag: member="EKF::dimu" ref="b0153795a1444b6968a86409c778d9ce" args="" --> 
     91int&nbsp;</td><td class="memItemRight" valign="bottom"><b>dimu</b></td></tr> 
     92 
     93<tr><td class="memItemLeft" nowrap align="right" valign="top"><a class="anchor" name="5e02efe86ee91e9c74b93b425fe060b9"></a><!-- doxytag: member="EKF::A" ref="5e02efe86ee91e9c74b93b425fe060b9" args="" --> 
     94mat&nbsp;</td><td class="memItemRight" valign="bottom"><b>A</b></td></tr> 
     95 
     96<tr><td class="memItemLeft" nowrap align="right" valign="top"><a class="anchor" name="dc87704284a6c0bca13bf51f4345a50a"></a><!-- doxytag: member="EKF::B" ref="dc87704284a6c0bca13bf51f4345a50a" args="" --> 
     97mat&nbsp;</td><td class="memItemRight" valign="bottom"><b>B</b></td></tr> 
     98 
     99<tr><td class="memItemLeft" nowrap align="right" valign="top"><a class="anchor" name="86a805cd6515872d1132ad0d6eb5dc13"></a><!-- doxytag: member="EKF::C" ref="86a805cd6515872d1132ad0d6eb5dc13" args="" --> 
     100mat&nbsp;</td><td class="memItemRight" valign="bottom"><b>C</b></td></tr> 
     101 
     102<tr><td class="memItemLeft" nowrap align="right" valign="top"><a class="anchor" name="d69f774ba3335c970c1c5b1d182f4dd1"></a><!-- doxytag: member="EKF::D" ref="d69f774ba3335c970c1c5b1d182f4dd1" args="" --> 
     103mat&nbsp;</td><td class="memItemRight" valign="bottom"><b>D</b></td></tr> 
     104 
     105<tr><td class="memItemLeft" nowrap align="right" valign="top"><a class="anchor" name="11d171dc0e0ab111c56a70f98b97b3ec"></a><!-- doxytag: member="EKF::R" ref="11d171dc0e0ab111c56a70f98b97b3ec" args="" --> 
     106<a class="el" href="classfsqmat.html">fsqmat</a>&nbsp;</td><td class="memItemRight" valign="bottom"><b>R</b></td></tr> 
     107 
     108<tr><td class="memItemLeft" nowrap align="right" valign="top"><a class="anchor" name="9b69015c800eb93f3ee49da23a6f55d9"></a><!-- doxytag: member="EKF::Q" ref="9b69015c800eb93f3ee49da23a6f55d9" args="" --> 
     109<a class="el" href="classfsqmat.html">fsqmat</a>&nbsp;</td><td class="memItemRight" valign="bottom"><b>Q</b></td></tr> 
     110 
     111<tr><td class="memItemLeft" nowrap align="right" valign="top"><a class="anchor" name="d422f51467c7a06174af2476d2826132"></a><!-- doxytag: member="EKF::_K" ref="d422f51467c7a06174af2476d2826132" args="" --> 
     112mat&nbsp;</td><td class="memItemRight" valign="bottom"><b>_K</b></td></tr> 
     113 
     114<tr><td class="memItemLeft" nowrap align="right" valign="top"><a class="anchor" name="30b7461989185d3d02cf42b8e2a37649"></a><!-- doxytag: member="EKF::_yp" ref="30b7461989185d3d02cf42b8e2a37649" args="" --> 
     115vec&nbsp;</td><td class="memItemRight" valign="bottom"><b>_yp</b></td></tr> 
     116 
     117<tr><td class="memItemLeft" nowrap align="right" valign="top"><a class="anchor" name="477dca07d91ea1a1f41d51bb0229934f"></a><!-- doxytag: member="EKF::_Ry" ref="477dca07d91ea1a1f41d51bb0229934f" args="" --> 
     118<a class="el" href="classfsqmat.html">fsqmat</a>&nbsp;</td><td class="memItemRight" valign="bottom"><b>_Ry</b></td></tr> 
     119 
     120<tr><td class="memItemLeft" nowrap align="right" valign="top"><a class="anchor" name="15f1a793210750a7e4642fcd948b24c5"></a><!-- doxytag: member="EKF::_iRy" ref="15f1a793210750a7e4642fcd948b24c5" args="" --> 
     121<a class="el" href="classfsqmat.html">fsqmat</a>&nbsp;</td><td class="memItemRight" valign="bottom"><b>_iRy</b></td></tr> 
     122 
     123<tr><td colspan="2"><br><h2>Friends</h2></td></tr> 
     124<tr><td class="memItemLeft" nowrap align="right" valign="top"><a class="anchor" name="86ba216243ed95bb46d80d88775d16af"></a><!-- doxytag: member="EKF::operator&lt;&lt;" ref="86ba216243ed95bb46d80d88775d16af" args="(std::ostream &amp;os, const KalmanFull &amp;kf)" --> 
     125std::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> 
     126 
    54127</table> 
    55128<hr><a name="_details"></a><h2>Detailed Description</h2> 
     
    59132Extended <a class="el" href="classKalman.html" title="Kalman filter with covariance matrices in square root form.">Kalman</a> Filter.  
    60133<p> 
    61 An approximation of the exact Bayesian filter with Gaussian noices and non-linear evolutions of their mean. <hr>The documentation for this class was generated from the following file:<ul> 
     134An approximation of the exact Bayesian filter with Gaussian noices and non-linear evolutions of their mean. <hr><h2>Member Function Documentation</h2> 
     135<a class="anchor" name="a892eff438aab2dd1a9e2efcb7fb5bdf"></a><!-- doxytag: member="EKF::bayes" ref="a892eff438aab2dd1a9e2efcb7fb5bdf" args="(const vec &amp;dt)=0" --> 
     136<div class="memitem"> 
     137<div class="memproto"> 
     138      <table class="memname"> 
     139        <tr> 
     140          <td class="memname">virtual void BM::bayes           </td> 
     141          <td>(</td> 
     142          <td class="paramtype">const vec &amp;&nbsp;</td> 
     143          <td class="paramname"> <em>dt</em>          </td> 
     144          <td>&nbsp;)&nbsp;</td> 
     145          <td width="100%"><code> [pure virtual, inherited]</code></td> 
     146        </tr> 
     147      </table> 
     148</div> 
     149<div class="memdoc"> 
     150 
     151<p> 
     152Incremental Bayes rule.  
     153<p> 
     154<dl compact><dt><b>Parameters:</b></dt><dd> 
     155  <table border="0" cellspacing="2" cellpadding="0"> 
     156    <tr><td valign="top"></td><td valign="top"><em>dt</em>&nbsp;</td><td>vector of input data </td></tr> 
     157  </table> 
     158</dl> 
     159 
     160</div> 
     161</div><p> 
     162<hr>The documentation for this class was generated from the following file:<ul> 
    62163<li>work/mixpp/bdm/estim/<a class="el" href="libKF_8h-source.html">libKF.h</a></ul> 
    63 <hr size="1"><address style="text-align: right;"><small>Generated on Sun Feb 17 16:14:19 2008 for mixpp by&nbsp; 
     164<hr size="1"><address style="text-align: right;"><small>Generated on Mon Feb 18 21:48:43 2008 for mixpp by&nbsp; 
    64165<a href="http://www.doxygen.org/index.html"> 
    65166<img src="doxygen.png" alt="doxygen" align="middle" border="0"></a> 1.5.3 </small></address>