Delayed learning on internal memory network and organizing internal states

Authors:
Toshinori Deguchi;Naohiro Ishii
Affiliations:
Gifu National College of Technology, Gifu, Japan;Aichi Institute of Technology, Aichi, Japan
Venue:
ISNN'06 Proceedings of the Third international conference on Advances in Neural Networks - Volume Part I
Year:
2006

Citing 2
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Delayed Learning and the Organized States

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Abstract

Elman presented a network with a context layer for the time-series processing. The context layer is connected to the hidden layer for the next calculation of the time series, which keeps the output of the hidden layer. In this paper, the context layer is reformed to the internal memory layer, which is connected from the hidden layer with the connection weights to make the internal memory. Then, the internal memory plays an important role of the learning of the time series. We developed a new learning algorithm, called the time-delayed back-propagation learning, for the internal memory. The ability of the network with the internal memory layer is demonstrated by applying the simple sinusoidal time-series.