A training pattern, consisting of an input vector $x=(x_1,x_2,x_3{)}^T$ and desired outputs

$t=(t_1,t_2,t_3{)}^T,$ is presented to the following neural network. What is the usual sequence

of events for training the network using the backpropagation algorithm?

a$.(1)$ calculate $y_j=f(H_j),(2)$ calculate $z_k=f(I_k),(3)$ update $w_{kj},(4)$ update $v_{ji}.$

b$.(1)$ calculate $y_j=f(H_j),(2)$ calculate $z_k=f(I_k),(3)$ update $v_{ji},(4)$ update $w_{kj}.$

c$.(1)$ calculate $y_j=f(H_j),(2)$ update $v_{ji},(3)$ calculate $z_k=f(I_k),(4)$ update $w_{kj}.$

d$.(1)$ calculate $z_k=f(I_k),(2)$ update $w_{kj},(3)$ calculate $y_j=f(H_j),(4)$ update $v_{ji}.$