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Bayes滤波器算法C++类说明文档,源码见Bayes滤波器算法

00065     }
00066 };
00067 
<a name="l00068"></a><a class="code" href="classBayesian__filter_1_1Counted__iterated__terminator.html">00068</a> <span class="keyword">class </span><a class="code" href="classBayesian__filter_1_1Counted__iterated__terminator.html">Counted_iterated_terminator</a> : <span class="keyword">public</span> <a class="code" href="classBayesian__filter_1_1Iterated__terminator.html">Iterated_terminator</a>
00069 <span class="comment">/*</span>
00070 <span class="comment"> * Termination condition with a simple fixed number of iterations </span>
00071 <span class="comment"> */</span>
00072 {
00073 <span class="keyword">public</span>:
<a name="l00074"></a><a class="code" href="classBayesian__filter_1_1Counted__iterated__terminator.html#a0">00074</a>     <a class="code" href="classBayesian__filter_1_1Counted__iterated__terminator.html#a0">Counted_iterated_terminator</a> (<a class="code" href="classBayesian__filter_1_1Iterated__observe__model.html">Iterated_observe_model</a>&amp; model, <span class="keywordtype">unsigned</span> iterations) :
00075         <a class="code" href="classBayesian__filter_1_1Counted__iterated__terminator.html#o0">m</a>(model), <a class="code" href="classBayesian__filter_1_1Counted__iterated__terminator.html#o1">i</a>(iterations)
00076     {}
00077     <span class="keywordtype">bool</span> <a class="code" href="classBayesian__filter_1_1Counted__iterated__terminator.html#a1">term_or_relinearize</a> (<span class="keyword">const</span> Iterated_covariance_scheme&amp; f);
<a name="l00078"></a><a class="code" href="classBayesian__filter_1_1Counted__iterated__terminator.html#o0">00078</a>     <a class="code" href="classBayesian__filter_1_1Iterated__observe__model.html">Iterated_observe_model</a>&amp; <a class="code" href="classBayesian__filter_1_1Counted__iterated__terminator.html#o0">m</a>;
<a name="l00079"></a><a class="code" href="classBayesian__filter_1_1Counted__iterated__terminator.html#o1">00079</a>     <span class="keywordtype">unsigned</span> <a class="code" href="classBayesian__filter_1_1Counted__iterated__terminator.html#o1">i</a>;
00080 };
00081 
00082 
00083 
<a name="l00084"></a><a class="code" href="classBayesian__filter_1_1Iterated__covariance__scheme.html">00084</a> <span class="keyword">class </span><a class="code" href="classBayesian__filter_1_1Iterated__covariance__scheme.html">Iterated_covariance_scheme</a> : <span class="keyword">public</span> <a class="code" href="classBayesian__filter_1_1Linrz__kalman__filter.html">Linrz_kalman_filter</a>
00085 {
00086 <span class="keyword">public</span>:
00087     <a class="code" href="classBayesian__filter_1_1Iterated__covariance__scheme.html#a0">Iterated_covariance_scheme</a> (size_t x_size, size_t z_initialsize = 0);
00088     <span class="comment">/* Initialised filter requries an addition iteration limit for the</span>
00089 <span class="comment">       observe algorithm */</span>
00090     <a class="code" href="classBayesian__filter_1_1Iterated__covariance__scheme.html">Iterated_covariance_scheme</a>&amp; <a class="code" href="classBayesian__filter_1_1Iterated__covariance__scheme.html#a1">operator= </a>(<span class="keyword">const</span> <a class="code" href="classBayesian__filter_1_1Iterated__covariance__scheme.html">Iterated_covariance_scheme</a>&amp;);
00091     <span class="comment">// Optimise copy assignment to only copy filter state</span>
00092 
00093     <span class="keywordtype">void</span> <a class="code" href="classBayesian__filter_1_1Iterated__covariance__scheme.html#a2">init</a> ();
00094     <span class="keywordtype">void</span> <a class="code" href="classBayesian__filter_1_1Iterated__covariance__scheme.html#a3">update</a> ();
00095     <a class="code" href="classBayesian__filter_1_1Bayes__base.html#w0">Float</a> <a class="code" href="classBayesian__filter_1_1Iterated__covariance__scheme.html#a4">predict</a> (<a class="code" href="classBayesian__filter_1_1Linrz__predict__model.html">Linrz_predict_model</a>&amp; f);
00096 
00097     <a class="code" href="classBayesian__filter_1_1Bayes__base.html#w0">Float</a> <a class="code" href="classBayesian__filter_1_1Iterated__covariance__scheme.html#a5">observe</a> (<a class="code" href="classBayesian__filter_1_1Linrz__uncorrelated__observe__model.html">Linrz_uncorrelated_observe_model</a>&amp; h, <a class="code" href="classBayesian__filter_1_1Iterated__terminator.html">Iterated_terminator</a>&amp; term, <span class="keyword">const</span> FM::Vec&amp; z);
00098     <a class="code" href="classBayesian__filter_1_1Bayes__base.html#w0">Float</a> <a class="code" href="classBayesian__filter_1_1Iterated__covariance__scheme.html#a5">observe</a> (<a class="code" href="classBayesian__filter_1_1Linrz__correlated__observe__model.html">Linrz_correlated_observe_model</a>&amp; h, <a class="code" href="classBayesian__filter_1_1Iterated__terminator.html">Iterated_terminator</a>&amp; term, <span class="keyword">const</span> FM::Vec&amp; z);
00099     <span class="comment">// Observe with iteration</span>
<a name="l00100"></a><a class="code" href="classBayesian__filter_1_1Iterated__covariance__scheme.html#a7">00100</a>     <a class="code" href="classBayesian__filter_1_1Bayes__base.html#w0">Float</a> <a class="code" href="classBayesian__filter_1_1Iterated__covariance__scheme.html#a5">observe</a> (<a class="code" href="classBayesian__filter_1_1Linrz__uncorrelated__observe__model.html">Linrz_uncorrelated_observe_model</a>&amp; h, <span class="keyword">const</span> FM::Vec&amp; z)
00101     {   <span class="comment">// Observe with default termination</span>
00102         <a class="code" href="classBayesian__filter_1_1Iterated__terminator.html">Iterated_terminator</a> term;
00103         <span class="keywordflow">return</span> <a class="code" href="classBayesian__filter_1_1Iterated__covariance__scheme.html#a5">observe</a> (h, term, z);
00104     }
<a name="l00105"></a><a class="code" href="classBayesian__filter_1_1Iterated__covariance__scheme.html#a8">00105</a>     <a class="code" href="classBayesian__filter_1_1Bayes__base.html#w0">Float</a> <a class="code" href="classBayesian__filter_1_1Iterated__covariance__scheme.html#a5">observe</a> (<a class="code" href="classBayesian__filter_1_1Linrz__correlated__observe__model.html">Linrz_correlated_observe_model</a>&amp; h, <span class="keyword">const</span> FM::Vec&amp; z)
00106     {   <span class="comment">// Observe with default termination</span>
00107         <a class="code" href="classBayesian__filter_1_1Iterated__terminator.html">Iterated_terminator</a> term;
00108         <span class="keywordflow">return</span> <a class="code" href="classBayesian__filter_1_1Iterated__covariance__scheme.html#a5">observe</a> (h, term, z);
00109     }
00110 
00111 <span class="keyword">public</span>:                     <span class="comment">// Exposed Numerical Results</span>
<a name="l00112"></a><a class="code" href="classBayesian__filter_1_1Iterated__covariance__scheme.html#o1">00112</a>     FM::SymMatrix <a class="code" href="classBayesian__filter_1_1Iterated__covariance__scheme.html#o0">S</a>, <a class="code" href="classBayesian__filter_1_1Iterated__covariance__scheme.html#o1">SI</a>;        <span class="comment">// Innovation Covariance and Inverse</span>
00113 
00114 <span class="keyword">protected</span>:                  <span class="comment">// Permenantly allocated temps</span>
<a name="l00115"></a><a class="code" href="classBayesian__filter_1_1Iterated__covariance__scheme.html#p0">00115</a>     FM::RowMatrix <a class="code" href="classBayesian__filter_1_1Iterated__covariance__scheme.html#p0">tempX</a>;
00116 
00117 <span class="keyword">protected</span>:                  <span class="comment">// allow fast operation if z_size remains constant</span>
<a name="l00118"></a><a class="code" href="classBayesian__filter_1_1Iterated__covariance__scheme.html#p1">00118</a>     size_t <a class="code" href="classBayesian__filter_1_1Iterated__covariance__scheme.html#p1">last_z_size</a>;
00119     <span class="keywordtype">void</span> <a class="code" href="classBayesian__filter_1_1Iterated__covariance__scheme.html#b0">observe_size</a> (size_t z_size);
00120                             <span class="comment">// Permenantly allocated temps</span>
<a name="l00121"></a><a class="code" href="classBayesian__filter_1_1Iterated__covariance__scheme.html#p2">00121</a>     FM::Vec <a class="code" href="classBayesian__filter_1_1Iterated__covariance__scheme.html#p2">s</a>;
<a name="l00122"></a><a class="code" href="classBayesian__filter_1_1Iterated__covariance__scheme.html#p3">00122</a>     FM::Matrix <a class="code" href="classBayesian__filter_1_1Iterated__covariance__scheme.html#p3">HxT</a>;
00123 };
00124 
00125 
00126 }<span class="comment">//namespace</span>
00127 <span class="preprocessor">#endif</span>
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