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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

00200     Likelihood_uncorrelated li;
00201 };
00202 
00203 <span class="comment">// General Linear Uncorrelated Addative and Likelihood observe model</span>
<a name="l00204"></a><a class="code" href="classBayesian__filter_1_1General__LiUnAd__observe__model.html">00204</a> <span class="keyword">class </span><a class="code" href="classBayesian__filter_1_1General__LiUnAd__observe__model.html">General_LiUnAd_observe_model</a> : <span class="keyword">public</span> <a class="code" href="classBayesian__filter_1_1Linear__uncorrelated__observe__model.html">Linear_uncorrelated_observe_model</a>, <span class="keyword">public</span> <a class="code" href="classBayesian__filter_1_1Likelihood__observe__model.html">Likelihood_observe_model</a>
00205 {
00206 <span class="keyword">public</span>:
<a name="l00207"></a><a class="code" href="classBayesian__filter_1_1General__LiUnAd__observe__model.html#a0">00207</a>     <a class="code" href="classBayesian__filter_1_1General__LiUnAd__observe__model.html#a0">General_LiUnAd_observe_model</a> (size_t x_size, size_t z_size) :
00208         <a class="code" href="classBayesian__filter_1_1Linear__uncorrelated__observe__model.html">Linear_uncorrelated_observe_model</a>(x_size, z_size),
00209         <a class="code" href="classBayesian__filter_1_1Likelihood__observe__model.html">Likelihood_observe_model</a>(z_size),
00210         li(z_size)
00211     {}
<a name="l00212"></a><a class="code" href="classBayesian__filter_1_1General__LiUnAd__observe__model.html#a1">00212</a>     <span class="keyword">virtual</span> <a class="code" href="classBayesian__filter_1_1Bayes__base.html#w0">Float</a> <a class="code" href="classBayesian__filter_1_1General__LiUnAd__observe__model.html#a1">L</a>(<span class="keyword">const</span> FM::Vec&amp; x) <span class="keyword">const</span>
00213     <span class="comment">// Definition of likelihood for addative noise model given zz</span>
00214     {   <span class="keywordflow">return</span> li.L(*<span class="keyword">this</span>, <a class="code" href="classBayesian__filter_1_1Likelihood__observe__model.html#p0">z</a>, <a class="code" href="classBayesian__filter_1_1Linear__uncorrelated__observe__model.html#a1">h</a>(x));
00215     }
<a name="l00216"></a><a class="code" href="classBayesian__filter_1_1General__LiUnAd__observe__model.html#a2">00216</a>     <span class="keyword">virtual</span> <span class="keywordtype">void</span> <a class="code" href="classBayesian__filter_1_1General__LiUnAd__observe__model.html#a2">Lz</a> (<span class="keyword">const</span> FM::Vec&amp; zz)
00217     <span class="comment">// Fix the observation zz about which to evaluate the Likelihood function</span>
00218     <span class="comment">// Zv is also fixed</span>
00219     {   Likelihood_observe_model::z = zz;
00220         li.Lz(*<span class="keyword">this</span>);
00221     }
00222 
00223 <span class="keyword">private</span>:
00224     General_LzUnAd_observe_model::Likelihood_uncorrelated li;
00225 };
00226 
00227 <span class="comment">// General Linearised Correlated Addative and Likelihood observe model</span>
<a name="l00228"></a><a class="code" href="classBayesian__filter_1_1General__LzCoAd__observe__model.html">00228</a> <span class="keyword">class </span><a class="code" href="classBayesian__filter_1_1General__LzCoAd__observe__model.html">General_LzCoAd_observe_model</a> : <span class="keyword">public</span> <a class="code" href="classBayesian__filter_1_1Linrz__correlated__observe__model.html">Linrz_correlated_observe_model</a>, <span class="keyword">public</span> <a class="code" href="classBayesian__filter_1_1Likelihood__observe__model.html">Likelihood_observe_model</a>
00229 {
00230 <span class="keyword">public</span>:
<a name="l00231"></a><a class="code" href="classBayesian__filter_1_1General__LzCoAd__observe__model.html#a0">00231</a>     <a class="code" href="classBayesian__filter_1_1General__LzCoAd__observe__model.html#a0">General_LzCoAd_observe_model</a> (size_t x_size, size_t z_size) :
00232         <a class="code" href="classBayesian__filter_1_1Linrz__correlated__observe__model.html">Linrz_correlated_observe_model</a>(x_size, z_size),
00233         <a class="code" href="classBayesian__filter_1_1Likelihood__observe__model.html">Likelihood_observe_model</a>(z_size),
00234         li(z_size)
00235     {}
<a name="l00236"></a><a class="code" href="classBayesian__filter_1_1General__LzCoAd__observe__model.html#a1">00236</a>     <span class="keyword">virtual</span> <a class="code" href="classBayesian__filter_1_1Bayes__base.html#w0">Float</a> <a class="code" href="classBayesian__filter_1_1General__LzCoAd__observe__model.html#a1">L</a>(<span class="keyword">const</span> FM::Vec&amp; x) <span class="keyword">const</span>
00237     <span class="comment">// Definition of likelihood for addative noise model given zz</span>
00238     {   <span class="keywordflow">return</span> li.L(*<span class="keyword">this</span>, <a class="code" href="classBayesian__filter_1_1Likelihood__observe__model.html#p0">z</a>, <a class="code" href="classBayesian__filter_1_1Parametised__observe__model.html#a1">h</a>(x));
00239     }
<a name="l00240"></a><a class="code" href="classBayesian__filter_1_1General__LzCoAd__observe__model.html#a2">00240</a>     <span class="keyword">virtual</span> <span class="keywordtype">void</span> <a class="code" href="classBayesian__filter_1_1General__LzCoAd__observe__model.html#a2">Lz</a> (<span class="keyword">const</span> FM::Vec&amp; zz)
00241     <span class="comment">// Fix the observation zz about which to evaluate the Likelihood function</span>
00242     <span class="comment">// Zv is also fixed</span>
00243     {   Likelihood_observe_model::z = zz;
00244         li.Lz(*<span class="keyword">this</span>);
00245     }
00246 
00247 <span class="keyword">private</span>:
<a name="l00248"></a><a class="code" href="classBayesian__filter_1_1General__LzCoAd__observe__model.html#n0">00248</a>     <span class="keyword">friend</span> <span class="keyword">class </span><a class="code" href="classBayesian__filter_1_1General__LiCoAd__observe__model.html">General_LiCoAd_observe_model</a>;
00249     <span class="keyword">struct </span>Likelihood_correlated
00250     {
00251         Likelihood_correlated(size_t z_size) :
00252             zInnov(z_size), Z_inv(z_size,z_size)
00253         {   zset = <span class="keyword">false</span>;
00254         }
00255         <span class="keyword">mutable</span> FM::Vec zInnov; <span class="comment">// Normailised innovation, temporary for L(x)</span>
00256         FM::SymMatrix Z_inv;    <span class="comment">// Inverse Noise Covariance</span>
00257         <a class="code" href="namespaceBayesian__filter__matrix.html#a0">Float</a> logdetZ;          <span class="comment">// log(det(Z)</span>
00258         <span class="keywordtype">bool</span> zset;  
00259         <span class="keyword">static</span> <a class="code" href="namespaceBayesian__filter__matrix.html#a0">Float</a> scaled_vector_square(<span class="keyword">const</span> FM::Vec&amp; v, <span class="keyword">const</span> FM::SymMatrix&amp; V);
00260         <a class="code" href="namespaceBayesian__filter__matrix.html#a0">Float</a> <a class="code" href="classBayesian__filter_1_1General__LzCoAd__observe__model.html#a1">L</a>(<span class="keyword">const</span> Correlated_addative_observe_model&amp; model, <span class="keyword">const</span> FM::Vec&amp; z, <span class="keyword">const</span> FM::Vec&amp; zp) <span class="keyword">const</span>;
00261         <span class="comment">// Definition of likelihood for addative noise model given zz</span>
00262         <span class="keywordtype">void</span> <a class="code" href="classBayesian__filter_1_1General__LzCoAd__observe__model.html#a2">Lz</a>(<span class="keyword">const</span> Correlated_addative_observe_model&amp; model);
00263     };
00264     Likelihood_correlated li;
00265 };
00266 
00267 <span class="comment">// General Linear Correlated Addative and Likelihood observe model</span>
<a name="l00268"></a><a class="code" href="classBayesian__filter_1_1General__LiCoAd__observe__model.html">00268</a> <span class="keyword">class </span><a class="code" href="classBayesian__filter_1_1General__LiCoAd__observe__model.html">General_LiCoAd_observe_model</a> : <span class="keyword">public</span> <a class="code" href="classBayesian__filter_1_1Linear__correlated__observe__model.html">Linear_correlated_observe_model</a>, <span class="keyword">public</span> <a class="code" href="classBayesian__filter_1_1Likelihood__observe__model.html">Likelihood_observe_model</a>
00269 {
00270 <span class="keyword">public</span>:
<a name="l00271"></a><a class="code" href="classBayesian__filter_1_1General__LiCoAd__observe__model.html#a0">00271</a>     <a class="code" href="classBayesian__filter_1_1General__LiCoAd__observe__model.html#a0">General_LiCoAd_observe_model</a> (size_t x_size, size_t z_size) :
00272         <a class="code" href="classBayesian__filter_1_1Linear__correlated__observe__model.html">Linear_correlated_observe_model</a>(x_size, z_size),
00273         <a class="code" href="classBayesian__filter_1_1Likelihood__observe__model.html">Likelihood_observe_model</a>(z_size),
00274         li(z_size)
00275     {}
<a name="l00276"></a><a class="code" href="classBayesian__filter_1_1General__LiCoAd__observe__model.html#a1">00276</a>     <span class="keyword">virtual</span> <a class="code" href="classBayesian__filter_1_1Bayes__base.html#w0">Float</a> <a class="code" href="classBayesian__filter_1_1General__LiCoAd__observe__model.html#a1">L</a>(<span class="keyword">const</span> FM::Vec&amp; x) <span class="keyword">const</span>
00277     <span class="comment">// Definition of likelihood for addative noise model given zz</span>
00278     {   <span class="keywordflow">return</span> li.L(*<span class="keyword">this</span>, <a class="code" href="classBayesian__filter_1_1Likelihood__observe__model.html#p0">z</a>, <a class="code" href="classBayesian__filter_1_1Linear__correlated__observe__model.html#a1">h</a>(x));
00279     }
<a name="l00280"></a><a class="code" href="classBayesian__filter_1_1General__LiCoAd__observe__model.html#a2">00280</a>     <span class="keyword">virtual</span> <span class="keywordtype">void</span> <a class="code" href="classBayesian__filter_1_1General__LiCoAd__observe__model.html#a2">Lz</a> (<span class="keyword">const</span> FM::Vec&amp; zz)
00281     <span class="comment">// Fix the observation zz about which to evaluate the Likelihood function</span>
00282     <span class="comment">// Zv is also fixed</span>
00283     {   Likelihood_observe_model::z = zz;
00284         li.Lz(*<span class="keyword">this</span>);
00285     }
00286 
00287 <span class="keyword">private</span>:
00288     General_LzCoAd_observe_model::Likelihood_correlated li;
00289 };
00290 
00291 
00292 }<span class="comment">// namespace</span>
00293 
00294 <span class="preprocessor">#endif</span>
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