Consider the classification problem based on the set of samples X: (a) Draw a graph of the data points labeled according to their classification. Is the problem solvable with one artificial neuron? If...

Consider the classification problem based on the set of samples X:

(a) Draw a graph of the data points labeled according to their classification. Is the problem solvable with one artificial neuron? If yes, graph the decision boundaries.

(b) Design a single - neuron perceptron to solve this problem. Determine the fi nal weight factors as a weight vector orthogonal to the decision boundary.

(c) Test your solution with all four samples.

(d) Using your network classify the following samples: ( − 2, 0), (1, 1), (0, 1), and ( − 1, − 2). (e) Which of the samples in (d) will always be classified the same way, and for which samples classification may vary depending on the solution?