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Figure 5.1 shows an architecture of a feed-forward artificial neural network with two inputs, two...

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Accounting

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Figure 5.1 shows an architecture of a feed-forward artificial neural network with two inputs, two hidden layer neurons, and one output neuron. The initial weights, biases, training inputs and output values are given to you as shown inside the figure. riguie 2.1 You are instructed to compute the new neuron weights for wk1,j1 and wj1,i1 after the first iteration of backpropagation for one training sample. You are expected to specify the learning rate as 0.5 and adopt a sigmoid function as the activation function. All results of calculations are required to be rounded to four decimal places. (10 marks) Figure 5.1 shows an architecture of a feed-forward artificial neural network with two inputs, two hidden layer neurons, and one output neuron. The initial weights, biases, training inputs and output values are given to you as shown inside the figure. riguie 2.1 You are instructed to compute the new neuron weights for wk1,j1 and wj1,i1 after the first iteration of backpropagation for one training sample. You are expected to specify the learning rate as 0.5 and adopt a sigmoid function as the activation function. All results of calculations are required to be rounded to four decimal places. (10 marks)

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