(NOTE: ANSWER MUST BE IN SOLVED FORM, NO PROGRAMMING)

Given the neural network below, calculate and show the weight changes that would be made by one step of BACKPROPAGATION for the training instance (X1.X2)=(0,05,0.10) and (Y1, Y2)=0.01,0.99). Assume that the hidden (H1 & H2) and output (Y1 & Y2) units use sigmoid functions, the network is being trained to minimize squared error, and the leaming rate is 1. Edges from constant b1 and b2 on the side indicate bias parameters. W1 W5 X1 H1 Y1 W6 W2 W3 W7 X2 H2 Y2 W4 W8 b1 b2 X1=0.05 b1=0.35 Y1=0.01 W1=0.15 W2=0.20 W3=0.25 W4=0.30 X2=0.10 b2=0.60 Y2=0.99 W5=0.40 W6=0.45 W7=0.50 W8=0.55