Presentation | 1997/2/6 Leaming performance of a neural network using a renewal mechanism with a threshold Yoshiyuki Matsuura, Yoshihiro Hayakawa, Kouji Nakajima, Yasuji Sawada, |
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PDF Download Page | PDF download Page Link |
Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | The efficiency of learning algorithm should be researched, when we use a neural network as an information processing machine. In this study, we propose a threshold renewal mechanism based on Deterministic Boltzmann Machine(DBM) leaming algorithm, and investigate the leaming performance of a neural network with the algorithm. As a result, the average of the updating accumulation of synapse weight is decreased by the factor 1/2-1/5 compared to that in ordinary DBM alghrithm. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | neural network / learning algorithm / threshold |
Paper # | NLP96-129,NC96-83 |
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Committee | NC |
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Conference Date | 1997/2/6(1days) |
Place (in Japanese) | (See Japanese page) |
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Topics (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) | Leaming performance of a neural network using a renewal mechanism with a threshold |
Sub Title (in English) | |
Keyword(1) | neural network |
Keyword(2) | learning algorithm |
Keyword(3) | threshold |
1st Author's Name | Yoshiyuki Matsuura |
1st Author's Affiliation | Institute of Electrical Communication, Tohoku University() |
2nd Author's Name | Yoshihiro Hayakawa |
2nd Author's Affiliation | Institute of Electrical Communication, Tohoku University |
3rd Author's Name | Kouji Nakajima |
3rd Author's Affiliation | Institute of Electrical Communication, Tohoku University |
4th Author's Name | Yasuji Sawada |
4th Author's Affiliation | Institute of Electrical Communication, Tohoku University |
Date | 1997/2/6 |
Paper # | NLP96-129,NC96-83 |
Volume (vol) | vol.96 |
Number (no) | 511 |
Page | pp.pp.- |
#Pages | 7 |
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