Note: In this question you should assume that the activation function of a perceptron is the step function. More specifically, this function:

outputs 0 if the weighted sum of inputs is LESS THAN 0 (not less than or equal).

outputs 1 if the weighted sum of inputs is greater than or equal to 0.

Design a perceptron that takes (in addition to the bias input) three Boolean inputs (i.e., inputs that are equal to 0 for false, and 1 for true), and outputs: 1 if at least two of the three inputs are true, 0 otherwise.

Note: In this question you should assume that the activation function of a perceptron is the same as the task above.

By (X => Y) we denote the boolean statement "If X then Y". Design a perceptron (i.e, an individual neuron) that takes in two Boolean inputs X and Y and outputs the Boolean value of (X => Y). As a reminder, 0 stands for "false" and 1 stands for "true". You should NOT worry about what your perceptron does when the input values are not 0 or 1