diff --git a/uebungen/aufgabe2/uebung2.py b/uebungen/aufgabe2/uebung2.py
index 79ea53c..3da05be 100644
--- a/uebungen/aufgabe2/uebung2.py
+++ b/uebungen/aufgabe2/uebung2.py
@@ -31,7 +31,6 @@ delta_L2 = np.ones((hid_size, out_size)) * 0.1
 w0 = np.random.random((inp_size, hid_size)) - 0.5
 w1 = np.random.random((hid_size, out_size)) - 0.5
 
-
 def multiply_learnrate(old, new):
     if old * new > 0:
         return 1.2
@@ -61,9 +60,10 @@ for i in range(10000):
     L1_error = np.matmul(L2_delta, w1.T)
     L1_delta = L1_error * deriv_sigmoid(L1)
 
-    # Gradienten
-    L2_grad_new = np.matmul(L1.T, L2_delta)
+    # Gradienten berechnen
     L1_grad_new = np.matmul(L0.T, L1_delta)
+    L2_grad_new = np.matmul(L1.T, L2_delta)
+    
 
     # Gewichte aktualisieren
 
@@ -72,10 +72,10 @@ for i in range(10000):
     delta_L2 = np.clip(
         delta_L2 * v_multiply_learnrate(L2_grad_old, L2_grad_new), 0, 50)
 
-    w1 -= np.sign(L2_grad_new) * delta_L2
     w0 -= np.sign(L1_grad_new) * delta_L1
+    w1 -= np.sign(L2_grad_new) * delta_L2
 
-    # Gradienten aktualisieren
+    # Gradienten aktualisieren bzw. kopieren
 
     L1_grad_old = np.copy(L1_grad_new)
     L2_grad_old = np.copy(L2_grad_new)
diff --git a/uebungen/aufgabe4/uebung4.py b/uebungen/aufgabe4/uebung4.py
index 6758009..a678971 100644
--- a/uebungen/aufgabe4/uebung4.py
+++ b/uebungen/aufgabe4/uebung4.py
@@ -36,7 +36,6 @@ def pool(image, stride=1, kernel_size=(2,2), transform=np.max, padding_size=(0,0
 
     next = np.zeros((height, width))
 
-    #'zero'|'mirror'
     for i in range(height):
         for j in range(width):
             # Translate upper left corner into original image space
@@ -45,7 +44,6 @@ def pool(image, stride=1, kernel_size=(2,2), transform=np.max, padding_size=(0,0
             # Retrieve image window 
             view = padded[y:y+kernel_size[0], x:x+kernel_size[1]]
 
-            #print(view)
             # Set pooled image value
             next[i][j] = transform(view)
 
@@ -60,10 +58,9 @@ weights = np.array([
 ])
 
 new1 = pool(image, kernel_size=(5,5), padding_size=(2,2), transform=convolute(weights))
-new2 = pool(new1, stride=3, kernel_size=(30,30), transform=np.max)
 
 fig = plt.figure()
 fig.canvas.manager.set_window_title("A Cat")
 
-plt.imshow(new2, cmap="gray")
+plt.imshow(new1, cmap="gray")
 plt.show()
\ No newline at end of file