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b) W14 W. 2 W56 WS W24 W25 W34 W35 W46 W56 X1 1 X2 X3 W14 WIS 04 05 06 01 0.2 -0.3 0.4
b) W14 W. 2 W56 WS W24 W25 W34 W35 W46 W56 X1 1 X2 X3 W14 WIS 04 05 06 01 0.2 -0.3 0.4 0.1 -0.5 0.2 -0.3 -0.2 -0.4 0.2 0.1 Figure shows a multilayer feed-forward neural network. Let the learning rate be 0.9. The initial weight and bias values of the network are given in the Table, along with the first training tuple, X = (x1,x2,43) = (1,0,1) with a class label of 1. Initial Input, Weight and Bias values are given as x, w and 6 in the table, respectively. Show the calculations for backpropagation, starting with the first training example, X. Calculate the input and output of each unit also compute the error of each unit and propagate it backward. Show the updates in the weight and bias values
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