C++ Neural Networks and Fuzzy Logic: Preface

Stability and Plasticity

We discuss now a few other considerations in neural network modeling by introducing short−term memory

and long−term memory concepts. Neural network training is usually done in an iterative way, meaning that

the procedure is repeated a certain number of times. These iterations are referred to as cycles. After each

cycle, the input used may remain the same or change, or the weights may remain the same or change. Such

change is based on the output of a completed cycle. If the number of cycles is not preset, and the network is

allowed to go through cycles until some other criterion is met, the question of whether or not the termination

of the iterative process occurs eventually, arises naturally.

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C++ Neural Networks and Fuzzy Logic:Preface

Stability and Plasticity

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