Presentation | 2007-10-18 Spatio-temporal analysis of synaptic weights in a self-organized neural network Hideyuki KATO, Takayuki KIMURA, Tohru IKEGUCHI, |
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Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | Recently, complex networks are studied in various fields of science. Neural networks are one of the most typical examples of complex networks. Although many kinds of analyses are applied to neural networks to understand network structures, almost of these analyses are static. On the other hand, recent studies on neuroscience reported that neural networks are dynamically self-organized by the spike-timing dependent synaptic plasticity (STDP). Then, it is necessary to analyze the neural network structures from a dynamical point of view. In this report, we show that the neural network with the STDP learning rule generates the small-world effect. We also show that the randomness of output spike sequences of the neural network increases if the neural network has the higher small-world effect. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | STDP / complex network / dynamics |
Paper # | CAS2007-36,NLP2007-64 |
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Committee | NLP |
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Conference Date | 2007/10/11(1days) |
Place (in Japanese) | (See Japanese page) |
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Paper Information | |
Registration To | Nonlinear Problems (NLP) |
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Language | ENG |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | Spatio-temporal analysis of synaptic weights in a self-organized neural network |
Sub Title (in English) | |
Keyword(1) | STDP |
Keyword(2) | complex network |
Keyword(3) | dynamics |
1st Author's Name | Hideyuki KATO |
1st Author's Affiliation | Graduate school of Science and Engineering, Saitama University() |
2nd Author's Name | Takayuki KIMURA |
2nd Author's Affiliation | Graduate school of Science and Engineering, Saitama University |
3rd Author's Name | Tohru IKEGUCHI |
3rd Author's Affiliation | Graduate school of Science and Engineering, Saitama University |
Date | 2007-10-18 |
Paper # | CAS2007-36,NLP2007-64 |
Volume (vol) | vol.107 |
Number (no) | 266 |
Page | pp.pp.- |
#Pages | 6 |
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