What would the following multilayer perceptron neural network predict for a new example where A_1 is 2 and A_2 is 3? Use the step/squashing activation function 0.5 1 -1 A -6 -1 2 -3.5 0.5
Added by William N.
Step 1
To predict the output of the multilayer perceptron neural network for the new example where \( A_1 = 2 \) and \( A_2 = 3 \), we will follow these steps: Show more…
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Consider MLP with one input, two layers, one neuron in each layer, and one output. The activation function of the first layer is f(n) = 2n, and the activation function of the second layer is f(2)(n) = 3n. The initial weights of the first and the second layers are respectively w(1) = 0 and w(2) = 0. There are no bias terms, so b(1) = 0 and b(2) = 0, and they are kept zero during training. Assume that we present the data point with x = 2 and y = 2 to the network. Perform one step of the Stochastic Gradient Descent algorithm by using the backpropagation algorithm, assuming the learning rate = 0.05. Use the MSE objective function, i.e. J = (y - a(2))^2. This means that you should calculate the updated weights.
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