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    r234 r255  
    2727<a name="l00021"></a>00021 <span class="preprocessor">#include "parametry_motoru.h"</span> 
    2828<a name="l00022"></a>00022  
    29 <a name="l00023"></a>00023 <span class="keyword">using namespace </span>itpp; 
     29<a name="l00023"></a>00023 <span class="keyword">using namespace </span>bdm; 
    3030<a name="l00024"></a>00024  
    3131<a name="l00025"></a>00025 <span class="keywordtype">double</span> minQ(<span class="keywordtype">double</span> Q); 
    3232<a name="l00026"></a>00026  
    33 <a name="l00032"></a><a class="code" href="classEKFfixed.html">00032</a> <span class="keyword">class </span><a class="code" href="classEKFfixed.html" title="Extended Kalman Filter with full matrices in fixed point arithmetic.">EKFfixed</a> : <span class="keyword">public</span> <a class="code" href="classBM.html" title="Bayesian Model of the world, i.e. all uncertainty is modeled by probabilities.">BM</a>, <span class="keyword">public</span> <a class="code" href="classBMcond.html" title="Conditional Bayesian Filter.">BMcond</a> { 
     33<a name="l00032"></a><a class="code" href="classEKFfixed.html">00032</a> <span class="keyword">class </span><a class="code" href="classEKFfixed.html" title="Extended Kalman Filter with full matrices in fixed point arithmetic.">EKFfixed</a> : <span class="keyword">public</span> <a class="code" href="classbdm_1_1BM.html" title="Bayesian Model of the world, i.e. all uncertainty is modeled by probabilities.">BM</a>, <span class="keyword">public</span> <a class="code" href="classbdm_1_1BMcond.html" title="Conditional Bayesian Filter.">BMcond</a> { 
    3434<a name="l00033"></a>00033 <span class="keyword">public</span>: 
    3535<a name="l00034"></a>00034 <span class="keywordtype">void</span> init_ekf(<span class="keywordtype">double</span> Tv); 
     
    6060<a name="l00059"></a>00059  
    6161<a name="l00060"></a>00060  <span class="keywordtype">long</span> temp30a[4]; <span class="comment">/* matrix [2,2] - temporary matrix for inversion */</span> 
    62 <a name="l00061"></a>00061  <a class="code" href="classenorm.html" title="Gaussian density with positive definite (decomposed) covariance matrix.">enorm&lt;fsqmat&gt;</a> E; 
     62<a name="l00061"></a>00061  <a class="code" href="classbdm_1_1enorm.html" title="Gaussian density with positive definite (decomposed) covariance matrix.">enorm&lt;fsqmat&gt;</a> E; 
    6363<a name="l00062"></a>00062  mat Ry; 
    6464<a name="l00063"></a>00063    
    6565<a name="l00064"></a>00064 <span class="keyword">public</span>: 
    66 <a name="l00066"></a><a class="code" href="classEKFfixed.html#64d7b1a39c27b1846bcd5628928748ef">00066</a>         <a class="code" href="classEKFfixed.html#64d7b1a39c27b1846bcd5628928748ef" title="Default constructor.">EKFfixed</a> ( <a class="code" href="classRV.html" title="Class representing variables, most often random variables.">RV</a> rvx,<a class="code" href="classRV.html" title="Class representing variables, most often random variables.">RV</a> <a class="code" href="classBMcond.html#9ba793c8ec453f04d372d17195ed8dec" title="Identificator of the conditioning variable.">rvc</a> ):<a class="code" href="classBM.html" title="Bayesian Model of the world, i.e. all uncertainty is modeled by probabilities.">BM</a>(rvx),<a class="code" href="classBMcond.html" title="Conditional Bayesian Filter.">BMcond</a>(rvc),E(rvx),Ry(2,2){ 
     66<a name="l00066"></a><a class="code" href="classEKFfixed.html#64d7b1a39c27b1846bcd5628928748ef">00066</a>         <a class="code" href="classEKFfixed.html#64d7b1a39c27b1846bcd5628928748ef" title="Default constructor.">EKFfixed</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_1BMcond.html#9a12750776d977408aada06a70093297" title="Identificator of the conditioning variable.">rvc</a> ):<a class="code" href="classbdm_1_1BM.html" title="Bayesian Model of the world, i.e. all uncertainty is modeled by probabilities.">BM</a>(rvx),<a class="code" href="classbdm_1_1BMcond.html" title="Conditional Bayesian Filter.">BMcond</a>(rvc),E(rvx),Ry(2,2){ 
    6767<a name="l00067"></a>00067         <span class="keywordtype">int</span> i; 
    6868<a name="l00068"></a>00068  <span class="keywordflow">for</span>(i=0;i&lt;16;i++){Q[i]=0;} 
     
    8484<a name="l00084"></a>00084 }; 
    8585<a name="l00086"></a>00086         <span class="keywordtype">void</span> <a class="code" href="classEKFfixed.html#ddf5334bc1207658fd53698fffbac028" title="Here dt = [yt;ut] of appropriate dimensions.">bayes</a> ( <span class="keyword">const</span> vec &amp;dt ); 
    86 <a name="l00088"></a><a class="code" href="classEKFfixed.html#085cf16c573eda32d8d03619c6c4b518">00088</a>         <a class="code" href="classepdf.html" title="Probability density function with numerical statistics, e.g. posterior density.">epdf</a>&amp; <a class="code" href="classEKFfixed.html#085cf16c573eda32d8d03619c6c4b518" title="dummy!">_epdf</a>(){<span class="keywordflow">return</span> E;}; 
     86<a name="l00088"></a><a class="code" href="classEKFfixed.html#085cf16c573eda32d8d03619c6c4b518">00088</a>         <a class="code" href="classbdm_1_1epdf.html" title="Probability density function with numerical statistics, e.g. posterior density.">epdf</a>&amp; <a class="code" href="classEKFfixed.html#085cf16c573eda32d8d03619c6c4b518" title="dummy!">_epdf</a>(){<span class="keywordflow">return</span> E;}; 
    8787<a name="l00089"></a><a class="code" href="classEKFfixed.html#c7fee79e75ad7f0c0e96c5a322cbf44e">00089</a>         <span class="keywordtype">void</span> <a class="code" href="classEKFfixed.html#c7fee79e75ad7f0c0e96c5a322cbf44e" title="Substitute val for rvc.">condition</a> ( <span class="keyword">const</span> vec &amp;Q0 ) { 
    8888<a name="l00090"></a>00090                  
     
    100100<a name="l00102"></a>00102  
    101101</pre></div></div> 
    102 <hr size="1"><address style="text-align: right;"><small>Generated on Thu Jan 15 10:50:26 2009 for mixpp by&nbsp; 
     102<hr size="1"><address style="text-align: right;"><small>Generated on Tue Jan 27 16:29:53 2009 for mixpp by&nbsp; 
    103103<a href="http://www.doxygen.org/index.html"> 
    104104<img src="doxygen.png" alt="doxygen" align="middle" border="0"></a> 1.5.6 </small></address>