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2015 | OriginalPaper | Buchkapitel

Simple Feature Quantities for Learning of Dynamic Binary Neural Networks

verfasst von : Ryuji Sato, Toshimichi Saito

Erschienen in: Neural Information Processing

Verlag: Springer International Publishing

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Abstract

This paper presents simple feature quantities for learning of dynamic binary neural networks. The teacher signal is a binary periodic orbit corresponding to control signal of switching circuits. The feature quantities characterize generation of spurious memories and stability of the teacher signal. We present a simple greedy search based algorithm where the two feature quantities are used as cost functions. Performing basic numerical experiments, the algorithm efficiency is confirmed.

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Metadaten
Titel
Simple Feature Quantities for Learning of Dynamic Binary Neural Networks
verfasst von
Ryuji Sato
Toshimichi Saito
Copyright-Jahr
2015
DOI
https://doi.org/10.1007/978-3-319-26532-2_25