We can represent the degree of error in an output node j in the nth data point (training example) by e_j(n)=d_j(n)-y_j(n), where d_j(n) is the desired target value for nth data point at node j, and y_j(n) is the value produced by the perceptron at node j when the nth data point is given as an input.
