Discrete-time cellular neural networks for associative memories with learning and forgetting capabilities

摘要

A synthesis procedure for associative memories using Discrete-Time Cellular Neural Networks (DTCNN's) with learning and forgetting capabilities is presented. The proposed design technique generates networks with the capability of learning new patterns and forgetting old ones without recomputing the whole interconnection matrix and the input vector.