Write a python program to solve the pattern discrimination task using a multi-layer perceptron (MLP), you would need to design a network with at least one hidden layer of artificial neurons in addition to the input and output layers. The input vectors should be constructed by taking the white boxes as 0.1 and the black boxes as 0.9, as specified in the question. You would also need to specify a learning rate parameter and a target error for the network. The learning rate determines the step size at which the network adjusts its weights during training, while the target error determines the desired level of accuracy for the network.

HOW DID YOU GENERATE THE Z-BASED PUZZLE ON 4 SIDES BY LOOKING AT THE IMAGE?

# Create the input vectors by taking the white boxes as 0.1 and the black boxes as 0.9

# for the z-based puzzle on 4 sides

x1 = np.array([[0.1, 0.1, 0.1, 0.1],

[0.1, 0.1, 0.1, 0.9],

[0.1, 0.1, 0.9, 0.1],

[0.1, 0.1, 0.9, 0.9],

[0.1, 0.9, 0.1, 0.1],

[0.1, 0.9, 0.1, 0.9],

[0.1, 0.9, 0.9, 0.1],

[0.1, 0.9, 0.9, 0.9]])