| We investigate the learning of de-terministic nite-state automata (DFA's) with recurrent networks with a single input neu-ron, where each input symbol is represented as a temporal pattern and strings as sequences of temporal patterns. We empirically demonstrate that obvious temporal encodings can make learning very diicult or even impossible. Based on… (More)

@inproceedings{Omlin1994TrainingRN,
title={Training Recurrent Neural Networks with Temporal Input Encodings},
author={C. W. Omlin and Cicely Giles and B. G. Horne and Laurens R. Leerink and T. Lin},
year={1994}
}