Presentation 2012-01-26
Analysis of Self-organizing Digital Spike Phase Maps
Narutoshi HORIMOTO, Takashi OGAWA, Toshimichi SAITO,
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Abstract(in English) This paper studies digital spike maps on lattice points and its learning algorithm. The maps can generate a variety of digital spike-trains and can be regarded as a simple version of the cellular automata. As a first step to analyze the rich dynamics, we calculate basic measures of the dynamics such as the number of periodic spike-trains. The learning algorithm has self-organizing functions and can extract embedded dynamics in noisy teacher signals. Performing basic numerical experiments, algorithm efficiency is confirmed. Our results may contribute to bridge between spiking neural systems and digital dynamical systems with rich applications.
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Keyword(in English) spiking neurons / digital spike-trains / self-organizing maps
Paper # NC2011-102
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Committee NC
Conference Date 2012/1/19(1days)
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Registration To Neurocomputing (NC)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Analysis of Self-organizing Digital Spike Phase Maps
Sub Title (in English)
Keyword(1) spiking neurons
Keyword(2) digital spike-trains
Keyword(3) self-organizing maps
1st Author's Name Narutoshi HORIMOTO
1st Author's Affiliation Faculty of Science and Engineering, Department of Electrical and Electronics Engineering, Hosei University()
2nd Author's Name Takashi OGAWA
2nd Author's Affiliation Faculty of Science and Engineering, Department of Electrical and Electronics Engineering, Hosei University
3rd Author's Name Toshimichi SAITO
3rd Author's Affiliation Faculty of Science and Engineering, Department of Electrical and Electronics Engineering, Hosei University
Date 2012-01-26
Paper # NC2011-102
Volume (vol) vol.111
Number (no) 419
Page pp.pp.-
#Pages 5
Date of Issue