b) Consider a perceptron that has three real-valued inputs and an output unit with a unit step activation function. The input sets area; = (1,0,1), a2= (0, -1, -1) and a3=(-1, -0.5,-1) and the target output for each of the training set is t= 0, t2= 1, t= 1, respectively and the initial weights, w)= (1, -1, 0) and the learning rate n= 0.1 i. Show how the perceptron learning rule would alter this neural network upon processing this training example up to the learned network.