A distance based network for sequence processing
David A. Calvert, Deborah Stacey, Mohamed S. Kamel · 2002
This work describes the development of an artificial neural network for sequence modeling and recall. The system described learns an initial data set and treats that as an exemplar for all later comparisons. One of the principles of this work was to design a system that takes advantage of the architectural features common to neural networks. These features are many simple storage locations (weights) and a collection of simple processing elements.