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We discussed the perceptron in class. Here is the architecture Inputs Weights Co Activation Function Input wo Input 1 Output tr U2 T2 Input 2 Figure 3: The perceptron. There are three inputs: bias (always-1), and inputs r, 2. The task is to determine weights wo,w, that will allow a correct firing of the perceptron. Here is what we're trying to learn: given , r2, what is t. We learned that we add a bias input InputsAnswer 0 0 that's always-1. So our table becomes: We are changinge wo,wso that the perceptron is TO 0 1 when t1 and 0 when t0. The perceptron is 1 when g), defined below, is positive 0 otherwise We discussed the perceptron in class. Here is the architecture Inputs Weights Co Activation Function Input wo Input 1 Output tr U2 T2 Input 2 Figure 3: The perceptron. There are three inputs: bias (always-1), and inputs r, 2. The task is to determine weights wo,w, that will allow a correct firing of the perceptron. Here is what we're trying to learn: given , r2, what is t. We learned that we add a bias input InputsAnswer 0 0 that's always-1. So our table becomes: We are changinge wo,wso that the perceptron is TO 0 1 when t1 and 0 when t0. The perceptron is 1 when g), defined below, is positive 0 otherwise