Presentation | 1997/3/17 Dynamics of Autoassociative Neural Networks Satoshi Morinaga, Kazuhiro Ishida, Shuji Yoshizawa, |
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Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | In this report, the dynamics of autoassociative analogue neural networks is analyzed theoretically. First, we show that the distance between the network state vector and the subspace Π_1 spanned by given patterns decreases in exponential order of time. And we show that the network dynamics is a gradient flow in Π_1. Then we prove that the dynamics outside of Π_1 is also a gradient flow. It means that the dynamics is not chaotic. Finally, we look into the dynamics in Π_1 and the dynamics toward Π_1 by computer simulations. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | associative memory / analogue neural networks / dynamics / chaos / gradient flow |
Paper # | NC96-125 |
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Committee | NC |
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Conference Date | 1997/3/17(1days) |
Place (in Japanese) | (See Japanese page) |
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Topics (in Japanese) | (See Japanese page) |
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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) | Dynamics of Autoassociative Neural Networks |
Sub Title (in English) | |
Keyword(1) | associative memory |
Keyword(2) | analogue neural networks |
Keyword(3) | dynamics |
Keyword(4) | chaos |
Keyword(5) | gradient flow |
1st Author's Name | Satoshi Morinaga |
1st Author's Affiliation | C&C Research Laboratories NEC Corporation() |
2nd Author's Name | Kazuhiro Ishida |
2nd Author's Affiliation | University of Tokyo |
3rd Author's Name | Shuji Yoshizawa |
3rd Author's Affiliation | University of Tokyo |
Date | 1997/3/17 |
Paper # | NC96-125 |
Volume (vol) | vol.96 |
Number (no) | 583 |
Page | pp.pp.- |
#Pages | 7 |
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