Consider the second iteration involves momentum please show step by step on how it affects the result

Consider a two-layer feedforward ANN with two inputs a and b, one hidden unit c, and one output unit d. This network has five weights (wca, Wcb, wco, Wde, wdo), where wxo represents the threshold weight for unit x. Initialize these weights to the values (1,.1,.1,.1,.1), then give their values after each of the first two training iterations of the BACKPROPAGATION algorithm. Assume learning rate .3, momentum = 0.9, incremental weight updates, and the following training examples