input: Write a function to create and simulate a 3-layer artificial neural network using Python and print the output. The function should take three layers as input: input_layer, hidden_layer, and output_layer, and print the result of passing the input through the network.
  
  assert simulate_neural_network([2, 3], [[0.1, 0.4], [0.8, 0.6], [0.3, 0.9]], [0.3, 0.7]) == "[0.9 2.1]"
  assert simulate_neural_network([1, 2], [[0.2, 0.5], [0.7, 0.3], [0.1, 0.8]], [0.4, 0.6]) == "[0.8 1.6]"
  assert simulate_neural_network([5, 1], [[0.9, 0.2], [0.4, 0.7], [0.6, 0.1]], [0.5, 0.5]) == "[5.4 1.1]"
  assert simulate_neural_network([0, 0], [[0.1, 0.4], [0.8, 0.6], [0.3, 0.9]], [0.3, 0.7]) == "[0. 0.]"
  assert simulate_neural_network([4, 5], [[0.6, 0.3], [0.2, 0.5], [0.4, 0.8]], [0.2, 0.8]) == "[4.4 4.8]"
output: def simulate_neural_network(input_layer, hidden_layer, output_layer):
      hidden_output = [sum(a * b for a, b in zip(input_layer, neuron)) for neuron in zip(*hidden_layer)]
      final_output = [sum(a * b for a, b in zip(hidden_output, neuron)) for neuron in zip(*output_layer)]
      print(f"[{final_output[0]} {final_output[1]}]")