Consider a Perceptron with 3 inputs, x1, x2, x3, and one output unit that uses the Signum function sgn(x) J 1 if x0 ( 1 if x 0 Assume initial weights w1 0 7, w2 0 9, w3 0 2, learning rate 0 3, and bias w4 0 5, Hence we (the desired output should be less than 0) WA W W have a) What is the output of the Perceptron given the inputs x1 1, x2 0, x3 1 x4 1 Show your work b) What are the updated weights' values after applying the Perceptron Learning Rule with the above input and teacher output 0 (means for the output 0 the desired output function is less than 0

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Consider a Perceptron with 3 inputs, x1, x2, x3, and one output unit that uses the Signum function. sgn(x)=. J+1 if x0 (-1 if

Consider a Perceptron with 3 inputs, x1, x2, x3, and one output unit that uses the Signum function. sgn(x)=. J+1 if x0 (-1 if x

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