C++ Neural Networks and Fuzzy Logic: Preface

ISBN: 1558515526   Pub Date: 06/01/95

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Table 5.9 shows that the network weight vector changed from an initial vector (0, 0) to the final weight vector

(1, 0) in eight iterations. This example is not of a network for pattern matching. If you think about it, you will

realize that the network is designed to fire if the first digit in the pattern is a 1, and not otherwise. An analogy

for this kind of a problem is determining if a given image contains a specific object in a specific part of the

image, such as a dot should occur in the letter i.

If the initial weights are chosen somewhat prudently and to make some particular relevance, then the speed of

operation can be increased in the sense of convergence being achieved with fewer iterations than otherwise.

Thus, encoding algorithms are important. We now present some of the encoding algorithms.