In a feed-forward neural network, the input layer has 4 neurons, the hidden layer 3 neurons and the output layer 2 neurons, all using the sigmoid activation. Inputs: [0.5, 0.8, 0.2, 0.6]. Input→hidden weights: 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]. Hidden→output weights: W4 = [0.4, 0.1, 0.3], W5 = [0.5, 0.2, 0.4]. What is the output of the output layer (rounded to two decimals)?
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Correct answer: A. [0.62, 0.68]
Explanation
Hidden net inputs: 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 → σ ≈ 0.63; 0.5(0.625) + 0.2(0.659) + 0.4(0.692) ≈ 0.721 → σ ≈ 0.67. The closest option is [0.62, 0.68].More Artificial Intelligence (AI) questions
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