Presentation | 1994/3/25 Self-organization of Velocity Selectivity Ken-ichiro Miura, Koji Kurata, Takashi Nagano, |
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Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | In this paper we present a mathematical analysis about the relation between the behavior and parameter of the model for motion detection proposed by one of the authors.Based on the analytical result a learning rule for acquiring velocity selectivity is proposed.The proposed learning rule is simple and plausible in the nervous system in that it is described by only local information.Numerical simulation results showed that the model can acquire the selecivity for the velocity of an input stimulus self-organizingly. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | velocity sensitve neural net. / self-learning rule |
Paper # | NC93-123 |
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Conference Information | |
Committee | NC |
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Conference Date | 1994/3/25(1days) |
Place (in Japanese) | (See Japanese page) |
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Paper Information | |
Registration To | Neurocomputing (NC) |
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Language | JPN |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | Self-organization of Velocity Selectivity |
Sub Title (in English) | |
Keyword(1) | velocity sensitve neural net. |
Keyword(2) | self-learning rule |
1st Author's Name | Ken-ichiro Miura |
1st Author's Affiliation | College of Engineering,Hosei University() |
2nd Author's Name | Koji Kurata |
2nd Author's Affiliation | Faculty of Engineering Science,Osaka University |
3rd Author's Name | Takashi Nagano |
3rd Author's Affiliation | College of Engnieering,Hosei University |
Date | 1994/3/25 |
Paper # | NC93-123 |
Volume (vol) | vol.93 |
Number (no) | 537 |
Page | pp.pp.- |
#Pages | 8 |
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