Answer Happy

The following parameters are given for a multilayer perceptron that consists of two inputs as X1 and X2, one hidden layer with two process elements and one output layer which produces two outputs as OT1 and OT2. In the hidden and output layers, the transfer function is selected as Sigmoid function (consider this function as f(x) = format). Both hidden and output layers have Bias contribution of 0.35 and 0.65, respectively. The learning rate (n) is selected as 0.5. The topology of the multilayer perceptron is given in Figure Q.4, and the initial values for weights are given in Table Q.4. 1+e Table Q.4. The ANN parameters. X2 X1 W1 W Target1 Target2 0.05 0.100.150.200.25 0.30 0.400.450.500.550.35 0.65 0.01 0.99 W2 W3 wa | WS W | W7 W8 | B1 B2 Input Layer Hidden Layer Output Layer W5 X1 W1 W2 H1 HT1 01T OT1 W6 W3 W4 W7 W8 02 T2 OT2 H2 HT2 X2 B2 B1 Figure Q.4. The proposed multilayer perceptron topology (a) Calculate H1, HT1, H2, HT2, 01, OT1, 02, OT2 values after one epoch (step) using forward pass.