1. Solve the three classification problems shown blew by drawing the decision boundary. Find weights and bias values that result in singleneuron perceptrons with the chosen decision boundaries. 2. Suppose that a given neural network does not fit a training set closely enough, even after backprop has been run to termination. How can the structure of the network be modified to fit the training set more accurately Consider the classification problem defined below p1=[11],t1=1&p2=[11],t2=1&p3=[00],t3=0&p4=[10],t4=0 i) Design a single neuron perceptron to solve this problem with initial weights W=[0 0] and b=0 ? ii) Classify the following inputs Covert the classification proble perceptron neural network model,w=3 and