Changeset 661 for applications

Timestamp:

10/15/09 00:10:19 (15 years ago)

Author:

smidl

Message:

doc

Location:

applications

Files:

• bdmtoolbox/mex/mexBM.cpp (modified) (1 diff)
• bdmtoolbox/tutorial/userguide/frg_estim.m (modified) (1 diff)
• dual/experiment/itermc.m (modified) (2 diffs)
• pmsm/cfg/mpf_test.cfg (modified) (1 diff)

applications/bdmtoolbox/mex/mexBM.cpp

@@ -70 +70 @@
                         //mexCallMATLAB(0, NULL, 1, &data, "dump");
                 } 
+                //! return correctly typed posterior (covariant return)
                 const mexEpdf& posterior() const  {
                         return est;

applications/bdmtoolbox/tutorial/userguide/frg_estim.m

@@ -28 +28 @@
 E.n = 20;                          % number of particles
 E.prior.class = 'eDirich';         % prior on non-linear part
-E.prior.beta  = [1 1]; % 
+E.prior.beta  = [2 1]; % 
 E.options ='logbounds,logll';
 E.name = 'MPF';

applications/dual/experiment/itermc.m

@@ -3 +3 @@
 c.sigma = 0.1;
 c.ndat = 50;
-
 yr = 1;
 
@@ -14 +13 @@
 C2.class='ce_ctrl';
 C2.yr   = yr;
-C2.b0   = -0.;
+C2.b0   = 0;
 C2.P0   = 1;
-
-c.controller = C1;
-M1=iterativemc(c);
-
-loss_exact = sum((M1.y-yr*ones(size(M1.y))).^2)
-loss_theory = c.ndat*c.sigma^2
-
-c.controller = C2;
-M2=iterativemc(c);
-
-loss_ce = sum((M2.y-yr*ones(size(M2.y))).^2)
 
 % monte carlo study
 n=100;
 losses=zeros(10,1);
-c.controller = C1;
 seeds=32000*rand(1,n);
 for i=1:n
+    c.b = randn();
     c.seed = seeds(i); 
+    c.controller = C1;
     Mmc=iterativemc(c);
     losses(i) = sum((Mmc.y-yr*ones(size(Mmc.y))).^2);
+    
+    c.controller = C2;
+    Mmc=iterativemc(c);
+    losses2(i) = sum((Mmc.y-yr*ones(size(Mmc.y))).^2);
 end
-[min(losses) mean(losses) max(losses)]
-    
+[min(losses) median(losses) max(losses)]
+[min(losses2) median(losses2) max(losses2)]
+

applications/pmsm/cfg/mpf_test.cfg

@@ -10 +10 @@
         {class="MPFpmsm"; 
         params = "pmsm107@cfg/zcu.cfg";
-        dQ=[0.17, 0.17, 0.00004, 1e-9];
+        dQ=[0.17, 0.17, 0.0004, 1e-5];
         dR=[0.06, 0.06];
         prior={class="euni";high=[4];low=[-4];};