Assumingthattheprocessingneuronsusearectifieractivationfunctions,thatthe input to the network is Neuron 1 = 0.3 and Neuron 2 = 0.6 and that the desired output for this input is Neuron 5 = 0.7 and Neuron 6 = 0.4: 8.7 Exercises 529 i. Calculatetheoutputgeneratedbythenetworkinresponsetothisinput. ii. Calculatethesumofsquarederrorsforthisnetworkonthisexample. iii. Calculate the values for each of the processing neurons in the network (i.e., 6, 5, 4, 3). iv. Using the values you calculated above, calculate the sensitivity of the error of the network to changes in each of the weights of the network (i.e., BE{Bw6,4, BE{Bw6,3, BE{Bw6,0, BE{Bw5,4, BE{Bw5,3, BE{Bw5,0, BE{Bw4,2, BE{Bw4,1, BE{Bw4,0, BE{Bw3,2, BE{Bw3,1, BE{Bw3,0). v. Assuming a learning rate of " 0.1, calculate the updated values for each of the weights in the network (w6,4,w6,3,w6,0,w5,4, w5,3, w5,0, w4,2,w4,1,w4,0, w3,2, w3,1, w3,0,) after the processing of this single training example. vi. Calculate the reduction in the sum of squared error of the network for this example using the new weights, compared with using the original weights