Changeset 323 for doc/html/kalman.html

Timestamp:

04/23/09 21:12:23 (16 years ago)

Author:

smidl

Message:

doc

Files:

• doc/html/kalman.html (modified) (3 diffs)

doc/html/kalman.html

@@ -65 +65 @@
 Kalman Filtering</a></h2>
 Kalman filtering is optimal estimation procedure for linear state space model: <p class="formulaDsp">
-<img class="formulaDsp" alt="\begin{eqnarray} x_t &amp;= &amp;A x_{t-1} + B u_{t} + v_t,\\ y_t &amp;= &amp;C x_{t} + D u_{t} + w_t, \end{eqnarray}" src="form_92.png">
+<img class="formulaDsp" alt="\begin{eqnarray} x_t &amp;= &amp;A x_{t-1} + B u_{t} + v_t,\\ y_t &amp;= &amp;C x_{t} + D u_{t} + w_t, \end{eqnarray}" src="form_100.png">
 <p>
- where <img class="formulaInl" alt="$ x_t $" src="form_93.png"> is the state, <img class="formulaInl" alt="$ y_t $" src="form_6.png"> is the system output, <img class="formulaInl" alt="$ A, B, C, D$" src="form_94.png"> are state matrices of appropriate dimensions, <img class="formulaInl" alt="$v_t, w_t$" src="form_95.png"> are zero mean Gaussian noises with covariance matrices <img class="formulaInl" alt="$Q, R$" src="form_96.png">, respectively.<p>
+ where <img class="formulaInl" alt="$ x_t $" src="form_101.png"> is the state, <img class="formulaInl" alt="$ y_t $" src="form_8.png"> is the system output, <img class="formulaInl" alt="$ A, B, C, D$" src="form_102.png"> are state matrices of appropriate dimensions, <img class="formulaInl" alt="$v_t, w_t$" src="form_103.png"> are zero mean Gaussian noises with covariance matrices <img class="formulaInl" alt="$Q, R$" src="form_104.png">, respectively.<p>
 Both prior and posterior densities on the state are Gaussian, i.e. of the class enorm.<p>
 There is a range of classes that implements this functionality, namely:<ul>
@@ -74 +74 @@
 Extended Kalman Filtering</a></h2>
 Extended Kalman filtering arise by linearization of non-linear state space model: <p class="formulaDsp">
-<img class="formulaDsp" alt="\begin{eqnarray} x_t &amp;= &amp;g( x_{t-1}, u_{t}) + v_t,\\ y_t &amp;= &amp;h( x_{t} , u_{t}) + w_t, \end{eqnarray}" src="form_97.png">
+<img class="formulaDsp" alt="\begin{eqnarray} x_t &amp;= &amp;g( x_{t-1}, u_{t}) + v_t,\\ y_t &amp;= &amp;h( x_{t} , u_{t}) + w_t, \end{eqnarray}" src="form_105.png">
 <p>
- where <img class="formulaInl" alt="$ g(), h() $" src="form_98.png"> are general non-linear functions which have finite derivatives. Remaining variables have the same meaning as in the Kalman Filter.<p>
+ where <img class="formulaInl" alt="$ g(), h() $" src="form_106.png"> are general non-linear functions which have finite derivatives. Remaining variables have the same meaning as in the Kalman Filter.<p>
 In order to use this class, the non-linear functions and their derivatives must be defined as an instance of class <code>diffbifn</code>.<p>
 Two classes are defined:<ul>
@@ -114 +114 @@
 }
 </pre></div> </div>
-<hr size="1"><address style="text-align: right;"><small>Generated on Thu Apr 9 14:33:20 2009 for mixpp by&nbsp;
+<hr size="1"><address style="text-align: right;"><small>Generated on Thu Apr 23 21:06:43 2009 for mixpp by&nbsp;
 <a href="http://www.doxygen.org/index.html">
 <img src="doxygen.png" alt="doxygen" align="middle" border="0"></a> 1.5.8 </small></address>