C++ Neural Networks and Fuzzy Logic: Preface

C++ Neural Networks and Fuzzy Logic

by Valluru B. Rao

MTBooks, IDG Books Worldwide, Inc.

ISBN: 1558515526   Pub Date: 06/01/95

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The top row in the table gives headings for the columns. They are, Item, I−1, I−2, I−3 (I−k being for input

layer neuron k); H−1, H−2 (for hidden layer neurons); and O−1, O−2, O−3 (for output layer neurons).

In the first column of the table, M−1 and M−2 refer to weight matrices as above. Where an entry is appended

with −H, like in Output −H, the information refers to the hidden layer. Similarly, −O refers to the output layer,

as in Activation + threshold −O.

The next iteration uses the following information from the previous iteration, which you can identify from

Table 7.1. The input pattern is ( 0.52, 0.75, 0.97 ), and the desired output pattern is ( 0.24, 0.17, 0.65). The

current weight matrices are as follows:

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

             0.6004   − 0.4

             0.2006     0.8001

           − 0.4992     0.3002

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

           −0.910       0.412      0.262

            0.096      −0.694     −0.734

The threshold values (or bias) for neurons in the hidden layer are 0.2008 and 0.3002, while those for the

output neurons are 0.1404, 0.2336, and 0.0616, respectively.

You can keep the learning parameters as 0.15 for connections between input and hidden layer neurons, and

0.2 for connections between the hidden layer neurons and output neurons, or you can slightly modify them.

Whether or not to change these two parameters is a decision that can be made perhaps at a later iteration,

having obtained a sense of how the process is converging.

If you are satisfied with the rate at which the computed output pattern is getting close to the target output

pattern, you would not change these learning rates. If you feel the convergence is much slower than you

would like, then the learning rate parameters can be adjusted slightly upwards. It is a subjective decision both

in terms of when (if at all) and to what new levels these parameters need to be revised.