Self-organizing digital spike interval maps

Authors:
Takashi Ogawa;Toshimichi Saito
Affiliations:
Hosei University, Tokyo, Japan;Hosei University, Tokyo, Japan
Venue:
ICONIP'11 Proceedings of the 18th international conference on Neural Information Processing - Volume Part II
Year:
2011

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Abstract

This paper studies digital spike interval maps and its learning algorithm. The map can output a variety of digital spike-trains. In order to learn a desired spike-train, two maps are switched by the contradiction detector and they evolve with self-organizing and growing functions. Performing basic numerical experiments for two examples, algorithm efficiency is confirmed.