C++ Neural Networks and Fuzzy Logic: Preface

Learning and Resonance

ART1 is the first neural network model based on adaptive resonance theory of Carpenter and Grossberg.

When you have a pair of patterns such that when one of them is input to a neural network the output turns out

to be the other pattern in the pair, and if this happens consistently in both directions, then you may describe it

as resonance. We discuss in Chapter 8 bidirectional associative memories and resonance. By the time training

is completed, and learning is through, many other pattern pairs would have been presented to the network as

well. If changes in the short−term memory do not disturb or affect the long−term memory, the network shows

adaptive resonance. The ART1 model is designed to maintain it. Note that this discussion relates largely to

stability.