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. © 2011 Springer-Verlag.
CITATION STYLE
Ogawa, T., & Saito, T. (2011). Self-organizing digital spike interval maps. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7063 LNCS, pp. 612–617). https://doi.org/10.1007/978-3-642-24958-7_71
Mendeley helps you to discover research relevant for your work.