In a feed-forward neural network with the following specifications : The input layer has 4 neurons, hidden layer has 3 neurons, and output layer has 2 neurons using the sigmoid activation function for given input values [0.5,0.8,0.2,0.6] as well as the initial weights for the connections. W1: [0.1,0.3,0.5,0.2] W2: [0.2,0.4,0.6,0.2] W3: [0.3,0.5,0.7,0.2] Input layer to hidden layer weights W4 : [0.4,0.1,0.3] W5 : [0.5,0.2,0.4] Hidden layer to output layer weights What is the output of the output layer when the given input values are passed through neural network? Round the answer to two decimal places:

1. A[0.62,0.68]
2. B[0.72,0.78]
3. C[0.82,0.88]
4. D[0.92,0.98]

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Correct answer: A. [0.62,0.68]

Explanation

Hidden nets: 0.51, 0.66, 0.81 → sigmoid 0.625, 0.659, 0.692. Output nets: 0.4(0.625) + 0.1(0.659) + 0.3(0.692) ≈ 0.524 and 0.5(0.625) + 0.2(0.659) + 0.4(0.692) ≈ 0.721 → sigmoid ≈ 0.63 and 0.67, closest to [0.62, 0.68].