Question

If e(m) denotes error for correction of weight then what is formula for error in perceptron learning model: w(m + 1) = w(m) + n(b(m) – s(m)) a(m), where b(m) is desired output, s(m) is actual output, a(m) is input vector and ‘w’ denotes weight

(a) e(m) = n(b(m) – s(m)) a(m)

(b) e(m) = n(b(m) – s(m))

(c) e(m) = (b(m) – s(m))

(d) none of the mentioned

This question was addressed to me by my college director while I was bunking the class.

This question is from Pattern Classification in portion Feedforward Neural Networks of Neural Networks

Answer 1

Right answer is (c) e(m) = (b(m) – s(m))

For explanation: Error is difference between desired and actual output.