MinorFix

Assignment5/randExample.m

@@ -1,7 +1,8 @@
 function randExample (trainingSet, characterToPlot)
 
 %Input:
-%HMMs that you can find using the TrainClassifiers function
+%trainingSet that you can find using the TrainClassifiersPierre function.
+%Structure containing the HMMs, and the classes objects.
 %
 %----------------------------------------------------
 %Code Authors:

Assignment5/randExample2.asv

@@ -0,0 +1,39 @@
+function randExample (trainingSet)
+
+%Input:
+%trainingSet that you can find using the TrainClassifiersPier function
+%
+%----------------------------------------------------
+%Code Authors:
+% Pierre Laurent
+% Christopher Norman
+%----------------------------------------------------
+vectorSize = 10000;
+HMMs = trainingSet.HMMs;
+classes = trainingSet.classes;
+A = [HMMs{1,:}];
+
+
+for i=1:9
+    randVec{i} = rand(HMMs{i}, vectorSize);
+end
+
+figure('Name','Plotting rand vectors obtained from each source','NumberTitle','off')
+
+
+for i = 1:9
+    x = 1 : size(HMMs, 2);
+    subplot(3,3,i)
+    stem(x, logprob(A, randVec{i}));
+    set(gca, 'XtickLabel', classes);
+    set(gca, 'Xtick', 1:size(HMMs, 2));
+    xlabel ('HMM index');
+    ylabel ('logprob(X, HMM)');
+    title (classes(i))
+end
+
+
+
+
+end
+

Assignment5/randExample2.m

@@ -1,7 +1,8 @@
 function randExample (trainingSet)
 
 %Input:
-%HMMs that you can find using the TrainClassifiers function
+%trainingSet that you can find using the TrainClassifiersPierre function.
+%Structure containing the HMMs, and the classes objects.
 %
 %----------------------------------------------------
 %Code Authors:
@@ -32,8 +33,5 @@ function randExample (trainingSet)
     title (classes(i))
 end
 
-
-
-
 end