| Presentation | 2002/3/8 Auto-Associative Memories Based on Recurrent Multilayer Perceptrons and Sparsely Interconnected Neural Networks Takeshi KAMIO, Mititada MORISUE, |
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| PDF Download Page | PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | Both quantized neural networks (QNNs) and sparsely interconnected neural networks (SINNs) are suitable for hardware implementation. However, quantized parameters and sparsely interconnected structure decrease the capabilities of QNNs and SINNs, respectively. In this report, we propose associative memories composed of recurrent multilayer perceptrons (RMLPs) with 3-valued weights and SINNs to improve their capabilities at a low cost. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | Auto-Associative Memories / Sparsely Interconnected Neural Networks / Recurrent Multilayer Perceptrons |
| Paper # | NLP2001-110 |
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| Conference Information | |
| Committee | NLP |
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| Conference Date | 2002/3/8(1days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | |
| Topics (in Japanese) | (See Japanese page) |
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| Paper Information | |
| Registration To | Nonlinear Problems (NLP) |
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| Language | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Auto-Associative Memories Based on Recurrent Multilayer Perceptrons and Sparsely Interconnected Neural Networks |
| Sub Title (in English) | |
| Keyword(1) | Auto-Associative Memories |
| Keyword(2) | Sparsely Interconnected Neural Networks |
| Keyword(3) | Recurrent Multilayer Perceptrons |
| 1st Author's Name | Takeshi KAMIO |
| 1st Author's Affiliation | Department of Information Machines and Interfaces, Faculty of Information Sciences, Hiroshima City University() |
| 2nd Author's Name | Mititada MORISUE |
| 2nd Author's Affiliation | Department of Information Machines and Interfaces, Faculty of Information Sciences, Hiroshima City University |
| Date | 2002/3/8 |
| Paper # | NLP2001-110 |
| Volume (vol) | vol.101 |
| Number (no) | 723 |
| Page | pp.pp.- |
| #Pages | 8 |
| Date of Issue | |