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Simple Feature Quantities for Learning of Dynamic Binary Neural Networks

  • Ryuji Sato
  • Toshimichi SaitoEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9489)

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.

Keywords

Dynamic neural networks Greedy search Switching circuits 

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.Hosei UniversityKoganeiJapan

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