Please answer 2A And 2C

2A. For the data shown in Table Q.2A, show the first iteration of back propagation algorithm in trying to compute the membership values for the input variables x1,x2 and x3 in the output region R1 and R2. Use a 332 neural network architecture. Assume a random set of weights for your neural network. 2B. Two companies bid for a contract. A committee has to review the estimates of those companies and give reports to its chairperson. The reviewed reports are evaluated on a non dimensional scale and assigned a weighted score that is represented by a fuzzy membership function, as illustrated by the two fuzzy sets B1 and B2, in Figure 2B. The chairperson is interested in the lowest bid, as well as a metric to measure the combined "best" score. For the logical union of the membership function shown we want to find the defuzzified quantity. Calculate the defuzzified value, z using centroid method. Figure 1: Q.2B 2C. Figure Q.2C(a) shows a neural network involving a single hidden neuron, for solving the XOR problem; this network may be viewed as an alternative to that given in Figure Q.2C(b). Show that the network of Figure Q.2C(a) solves the XOR problem by constructing i) decision regions, and ii) a truth table for the network. Figure: Q.2C