diff --git a/matlab/cls_ConfusionMatrix.m b/matlab/cls_ConfusionMatrix.m
new file mode 100644
index 0000000..f5081fd
--- /dev/null
+++ b/matlab/cls_ConfusionMatrix.m
@@ -0,0 +1,13 @@
+function M = cls_ConfusionMatrix(GT, T)
+
+%calculate the classes (unique elements in the GT array)
+C = unique(GT);
+nc = length(C);        %calculate the number of classes
+M = zeros(nc);      %allocate space for the confusion matrix
+
+%for each class
+for ci = 1:nc
+    for cj = 1:nc
+        M(ci, cj) = nnz((GT == C(ci)) .* (T == C(cj)));
+    end
+end
\ No newline at end of file
diff --git a/matlab/cls_MeanClassFeatures.m b/matlab/cls_MeanClassFeatures.m
new file mode 100644
index 0000000..2a04fe0
--- /dev/null
+++ b/matlab/cls_MeanClassFeatures.m
@@ -0,0 +1,12 @@
+function S = cls_MeanClassFeatures(F, T)
+%Calculates the mean set of features for each class given the feature matrix F and targets T
+
+C = unique(T);                          %get the class IDs
+nc = length(C);
+
+S = zeros(nc, size(F, 2));              %allocate space for the mean feature vectors
+for c = 1:nc                            %for each class
+    S(c, :) = mean(F(T == C(c), :));    %calculate the mean feature vector for class c
+end
+	
+S = S';
\ No newline at end of file
diff --git a/matlab/cls_PlotConfusionMatrix.m b/matlab/cls_PlotConfusionMatrix.m
new file mode 100644
index 0000000..a2dd163
--- /dev/null
+++ b/matlab/cls_PlotConfusionMatrix.m
@@ -0,0 +1,13 @@
+function cls_PlotConfusionMatrix(M)
+
+
+%normalize each row by its column
+sum_cols = repmat(sum(M, 1), size(M, 1), 1);
+Mc = M ./ sum_cols;
+subplot(2, 1, 1),
+bar(Mc');
+
+sum_rows = repmat(sum(M, 2), 1, size(M, 2));
+Mr = M ./ sum_rows;
+subplot(2, 1, 2),
+bar(Mr);
\ No newline at end of file
--
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