diff --git a/ex7/findClosestCentroids.m b/ex7/findClosestCentroids.m
index 52f6d8e..dd068a6 100644
--- a/ex7/findClosestCentroids.m
+++ b/ex7/findClosestCentroids.m
@@ -1,7 +1,7 @@
 function idx = findClosestCentroids(X, centroids)
 %FINDCLOSESTCENTROIDS computes the centroid memberships for every example
 %   idx = FINDCLOSESTCENTROIDS (X, centroids) returns the closest centroids
-%   in idx for a dataset X where each row is a single example. idx = m x 1 
+%   in idx for a dataset X where each row is a single example. idx = m x 1
 %   vector of centroid assignments (i.e. each entry in range [1..K])
 %
 
@@ -15,17 +15,26 @@ idx = zeros(size(X,1), 1);
 % Instructions: Go over every example, find its closest centroid, and store
 %               the index inside idx at the appropriate location.
 %               Concretely, idx(i) should contain the index of the centroid
-%               closest to example i. Hence, it should be a value in the 
+%               closest to example i. Hence, it should be a value in the
 %               range 1..K
 %
 % Note: You can use a for-loop over the examples to compute this.
 %
 
+for i = 1:size(X,1)
 
+  idx(i) = 0;  % unassigned yet
+  best_distance = Inf;
 
+  for k = 1:K
+    distance = norm(X(i,:) - centroids(k,:))^2;
+    if distance < best_distance
+      idx(i) = k;
+      best_distance = distance;
+    end
+  end
 
-
-
+end
 
 % =============================================================