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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

<a name="l00097"></a><a class="code" href="classBayesian__filter_1_1Simple__linear__correlated__observe__model.html">00097</a> <span class="keyword">class </span><a class="code" href="classBayesian__filter_1_1Simple__linear__correlated__observe__model.html">Simple_linear_correlated_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>
00098 <span class="comment">// Linear observe model initialised from model matricies</span>
00099 {
00100 <span class="keyword">public</span>:
00101     <a class="code" href="classBayesian__filter_1_1Simple__linear__correlated__observe__model.html#a0">Simple_linear_correlated_observe_model</a> (<span class="keyword">const</span> FM::Matrix&amp; Hx_init, <span class="keyword">const</span> FM::SymMatrix&amp; Z_init);
00102     <span class="comment">// Precondition: Hx, Z are conformantly dimensioned (not checked)</span>
00103 };
00104 
<a name="l00105"></a><a class="code" href="classBayesian__filter_1_1Simple__linear__uncorrelated__observe__model.html">00105</a> <span class="keyword">class </span><a class="code" href="classBayesian__filter_1_1Simple__linear__uncorrelated__observe__model.html">Simple_linear_uncorrelated_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>
00106 <span class="comment">// Linear observe model initialised from model matricies</span>
00107 {
00108 <span class="keyword">public</span>:
00109     <a class="code" href="classBayesian__filter_1_1Simple__linear__uncorrelated__observe__model.html#a0">Simple_linear_uncorrelated_observe_model</a> (<span class="keyword">const</span> FM::Matrix&amp; Hx_init, <span class="keyword">const</span> FM::Vec&amp; Zv_init);
00110     <span class="comment">// Precondition: Hx, Zv are conformantly dimensioned (not checked)</span>
00111 };
00112 
00113 
00114 
00115 <span class="comment">/*</span>
00116 <span class="comment"> * Model Adaptors: Constructed with a reference to another model</span>
00117 <span class="comment"> */</span>
00118 
00119 
<a name="l00120"></a><a class="code" href="classBayesian__filter_1_1Adapted__Correlated__addative__observe__model.html">00120</a> <span class="keyword">class </span><a class="code" href="classBayesian__filter_1_1Adapted__Correlated__addative__observe__model.html">Adapted_Correlated_addative_observe_model</a> : <span class="keyword">public</span> <a class="code" href="classBayesian__filter_1_1Correlated__addative__observe__model.html">Correlated_addative_observe_model</a>
00121 <span class="comment">/*</span>
00122 <span class="comment"> * Adapt Uncorrelated_addative_observe_model to an equivilent</span>
00123 <span class="comment"> * Correlated_addative_observe_model_adaptor</span>
00124 <span class="comment"> */</span>
00125 {
00126 <span class="keyword">public</span>:
00127     <a class="code" href="classBayesian__filter_1_1Adapted__Correlated__addative__observe__model.html#a0">Adapted_Correlated_addative_observe_model</a> (<a class="code" href="classBayesian__filter_1_1Uncorrelated__addative__observe__model.html">Uncorrelated_addative_observe_model</a>&amp; adapt);
<a name="l00128"></a><a class="code" href="classBayesian__filter_1_1Adapted__Correlated__addative__observe__model.html#a1">00128</a>     <span class="keyword">const</span> FM::Vec&amp; <a class="code" href="classBayesian__filter_1_1Adapted__Correlated__addative__observe__model.html#a1">h</a>(<span class="keyword">const</span> FM::Vec&amp; x)<span class="keyword"> const</span>
00129 <span class="keyword">    </span>{
00130         <span class="keywordflow">return</span> unc.<a class="code" href="classBayesian__filter_1_1Parametised__observe__model.html#a1">h</a>(x);
00131     }
<a name="l00132"></a><a class="code" href="classBayesian__filter_1_1Adapted__Correlated__addative__observe__model.html#a2">00132</a>     <span class="keyword">inline</span> <span class="keywordtype">void</span> <a class="code" href="classBayesian__filter_1_1Adapted__Correlated__addative__observe__model.html#a2">normalise</a> (FM::Vec&amp; z_denorm, <span class="keyword">const</span> FM::Vec&amp; z_from)<span class="keyword"> const</span>
00133 <span class="keyword">    </span>{
00134         unc.<a class="code" href="classBayesian__filter_1_1Parametised__observe__model.html#a2">normalise</a> (z_denorm, z_from);
00135     };
00136 <span class="keyword">private</span>:
00137     Uncorrelated_addative_observe_model&amp; unc;
00138 };
00139 
<a name="l00140"></a><a class="code" href="classBayesian__filter_1_1Adapted__Linrz__correlated__observe__model.html">00140</a> <span class="keyword">class </span><a class="code" href="classBayesian__filter_1_1Adapted__Linrz__correlated__observe__model.html">Adapted_Linrz_correlated_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>
00141 <span class="comment">/*</span>
00142 <span class="comment"> * Adapt Linrz_uncorrelated_observe_model to an equivilent</span>
00143 <span class="comment"> * Linrz_correlated_observe_model</span>
00144 <span class="comment"> */</span>
00145 {
00146 <span class="keyword">public</span>:
00147     <a class="code" href="classBayesian__filter_1_1Adapted__Linrz__correlated__observe__model.html#a0">Adapted_Linrz_correlated_observe_model</a> (<a class="code" href="classBayesian__filter_1_1Linrz__uncorrelated__observe__model.html">Linrz_uncorrelated_observe_model</a>&amp; adapt);
<a name="l00148"></a><a class="code" href="classBayesian__filter_1_1Adapted__Linrz__correlated__observe__model.html#a1">00148</a>     <span class="keyword">const</span> FM::Vec&amp; <a class="code" href="classBayesian__filter_1_1Adapted__Linrz__correlated__observe__model.html#a1">h</a>(<span class="keyword">const</span> FM::Vec&amp; x)<span class="keyword"> const</span>
00149 <span class="keyword">    </span>{
00150         <span class="keywordflow">return</span> <a class="code" href="classBayesian__filter_1_1Adapted__Linrz__correlated__observe__model.html#p0">unc</a>.<a class="code" href="classBayesian__filter_1_1Parametised__observe__model.html#a1">h</a>(x);
00151     }
<a name="l00152"></a><a class="code" href="classBayesian__filter_1_1Adapted__Linrz__correlated__observe__model.html#a2">00152</a>     <span class="keyword">inline</span> <span class="keywordtype">void</span> <a class="code" href="classBayesian__filter_1_1Adapted__Linrz__correlated__observe__model.html#a2">normalise</a> (FM::Vec&amp; z_denorm, <span class="keyword">const</span> FM::Vec&amp; z_from)<span class="keyword"> const</span>
00153 <span class="keyword">    </span>{
00154         <a class="code" href="classBayesian__filter_1_1Adapted__Linrz__correlated__observe__model.html#p0">unc</a>.<a class="code" href="classBayesian__filter_1_1Parametised__observe__model.html#a2">normalise</a> (z_denorm, z_from);
00155     };
00156 <span class="keyword">protected</span>:
<a name="l00157"></a><a class="code" href="classBayesian__filter_1_1Adapted__Linrz__correlated__observe__model.html#p0">00157</a>     <a class="code" href="classBayesian__filter_1_1Linrz__uncorrelated__observe__model.html">Linrz_uncorrelated_observe_model</a>&amp; <a class="code" href="classBayesian__filter_1_1Adapted__Linrz__correlated__observe__model.html#p0">unc</a>;
00158 };
00159 
00160 
00161 <span class="comment">/*</span>
00162 <span class="comment"> * Genereal Models: Include properties of more then on observe model.</span>
00163 <span class="comment"> */</span>
00164 
00165 <span class="comment">// General Linearised Uncorrelated Addative and Likelihood observe model</span>
<a name="l00166"></a><a class="code" href="classBayesian__filter_1_1General__LzUnAd__observe__model.html">00166</a> <span class="keyword">class </span><a class="code" href="classBayesian__filter_1_1General__LzUnAd__observe__model.html">General_LzUnAd_observe_model</a> : <span class="keyword">public</span> <a class="code" href="classBayesian__filter_1_1Linrz__uncorrelated__observe__model.html">Linrz_uncorrelated_observe_model</a>, <span class="keyword">public</span> <a class="code" href="classBayesian__filter_1_1Likelihood__observe__model.html">Likelihood_observe_model</a>
00167 {
00168 <span class="keyword">public</span>:
<a name="l00169"></a><a class="code" href="classBayesian__filter_1_1General__LzUnAd__observe__model.html#a0">00169</a>     <a class="code" href="classBayesian__filter_1_1General__LzUnAd__observe__model.html#a0">General_LzUnAd_observe_model</a> (size_t x_size, size_t z_size) :
00170         <a class="code" href="classBayesian__filter_1_1Linrz__uncorrelated__observe__model.html">Linrz_uncorrelated_observe_model</a>(x_size, z_size),
00171         <a class="code" href="classBayesian__filter_1_1Likelihood__observe__model.html">Likelihood_observe_model</a>(z_size),
00172         li(z_size)
00173     {}
<a name="l00174"></a><a class="code" href="classBayesian__filter_1_1General__LzUnAd__observe__model.html#a1">00174</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__LzUnAd__observe__model.html#a1">L</a>(<span class="keyword">const</span> FM::Vec&amp; x) <span class="keyword">const</span>
00175     <span class="comment">// Definition of likelihood for addative noise model given zz</span>
00176     {   <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));
00177     }
<a name="l00178"></a><a class="code" href="classBayesian__filter_1_1General__LzUnAd__observe__model.html#a2">00178</a>     <span class="keyword">virtual</span> <span class="keywordtype">void</span> <a class="code" href="classBayesian__filter_1_1General__LzUnAd__observe__model.html#a2">Lz</a> (<span class="keyword">const</span> FM::Vec&amp; zz)
00179     <span class="comment">// Fix the observation zz about which to evaluate the Likelihood function</span>
00180     <span class="comment">// Zv is also fixed</span>
00181     {   Likelihood_observe_model::z = zz;
00182         li.Lz(*<span class="keyword">this</span>);
00183     }
00184 <span class="keyword">private</span>:
<a name="l00185"></a><a class="code" href="classBayesian__filter_1_1General__LzUnAd__observe__model.html#n0">00185</a>     <span class="keyword">friend</span> <span class="keyword">class </span><a class="code" href="classBayesian__filter_1_1General__LiUnAd__observe__model.html">General_LiUnAd_observe_model</a>;
00186     <span class="keyword">struct </span>Likelihood_uncorrelated
00187     {
00188         Likelihood_uncorrelated(size_t z_size) :
00189             zInnov(z_size), Zv_inv(z_size)
00190         {   zset = <span class="keyword">false</span>;
00191         }
00192         <span class="keyword">mutable</span> FM::Vec zInnov; <span class="comment">// Normailised innovation, temporary for L(x)</span>
00193         FM::Vec Zv_inv;         <span class="comment">// Inverse Noise Covariance given zz</span>
00194         <a class="code" href="namespaceBayesian__filter__matrix.html#a0">Float</a> logdetZ;          <span class="comment">// log(det(Z))</span>
00195         <span class="keywordtype">bool</span> zset;
00196         <a class="code" href="namespaceBayesian__filter__matrix.html#a0">Float</a> <a class="code" href="classBayesian__filter_1_1General__LzUnAd__observe__model.html#a1">L</a>(<span class="keyword">const</span> Uncorrelated_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>;
00197         <span class="comment">// Definition of likelihood for addative noise model given zz</span>
00198         <span class="keywordtype">void</span> <a class="code" href="classBayesian__filter_1_1General__LzUnAd__observe__model.html#a2">Lz</a>(<span class="keyword">const</span> Uncorrelated_addative_observe_model&amp; model);
00199     };