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Consider a two-layer feedforward ANN with two inputs and , one hidden unit , and one output unit . This network has 5 weights (
Consider a two-layer feedforward ANN with two inputs and , one hidden unit , and one output unit . This network has 5 weights (a, b, 0, c , 0), where 0 represents the threshold weight for unit . Initialize these weights to the values (0.1, 0.1, 0.1, 0.1, 0.1), then give their values after each of the first two training iterations of the sum of squared errors-based Backpropagation algorithm. Assume learning rate = 0.3, momentum = 0.9, incremental weight updates, and the following training examples:
a | b | d |
1 | 0 | 1 |
0 | 1 | 0 |
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