E3.2 Consider the following prototype patterns. i. ii. iii. P1 = P2 = 10.5. [1] Find and sketch a decision boundary for a perceptron network that will recognize these two vectors. Find weights and bias which will produce the decision boundary you found in part i, and sketch the network diagram. Calculate the network output for the following input. Is the network response (decision) reasonable? Explain. p = [2] iv. V. Design a Hamming network to recognize the two prototype vectors above. Calculate the network output for the Hamming network with the input vector given in part iii, showing all steps. Does the Hamming network produce the same decision as the perceptron? Explain why or why not. Which network is better suited to this problem? Explain.

E3.2 Consider the following prototype patterns. i. ii. iii. P1 = P2 = 10.5. [1] Find and sketch a decision boundary for a perceptron network that will recognize these two vectors. Find weights and bias which will produce the decision boundary you found in part i, and sketch the network diagram. Calculate the network output for the following input. Is the network response (decision) reasonable? Explain. p = [2] iv. V. Design a Hamming network to recognize the two prototype vectors above. Calculate the network output for the Hamming network with the input vector given in part iii, showing all steps. Does the Hamming network produce the same decision as the perceptron? Explain why or why not. Which network is better suited to this problem? Explain.