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d) Figure 6 represents a feed-forward neural network with one hidden layer: 1 5 2 Figure 6: Feed-forward neural network with one hidden layer A weight on connection between nodes i and j is denoted by w, such as w is the weight on the connection between nodes 1 and 3. Table 1 lists all the weights in the network. Table 1: All weights in the network W13 = -2 W:s = 1 W = 3 Was = -1 W4 = 4 W36 = -1 W3 = -1 W46 = 1 Each of the nodes 3, 4, 5 and 6 uses the following activation function: 4 (v) 1 if v 20 O otherwise where y denotes the weighted sum of a node. Each of the input nodes (1 and 2) can only receive binary values (either 0 or 1). Calculate the output of the network (ys and y.) for the input patterns P1, P3 and P4: P1 P3 P4 Pattern Node P2 1 0 0 1 Node 2 0 0 1 1