Self-organizing Digital Spike Interval Maps

Takashi Ogawa, Toshimichi Saito

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.