C++ Neural Networks and Fuzzy Logic: Preface

M−1 Matrix of weights from input layer to hidden layer

       0.6     − 0.4

       0.2       0.8

     − 0.5       0.3

M−2 Matrix of weights from hidden layer to output layer

     −0.90       0.43       0.25

      0.11     − 0.67     − 0.75

The threshold values (or bias) for neurons in the hidden layer are 0.2 and 0.3, while those for the output

neurons are 0.15, 0.25, and 0.05, respectively.

Table 7.1 presents all the results of calculations done in the first iteration. You will see modified or new

weight matrices and threshold values. You will use these and the original input vector and the desired output

vector to carry out the next iteration.

Table 7.1 Backpropagation Calculations