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| Presentation | 2019-10-12 10:00 Stability of Periodic Orbits in 3-Layer Dynamic Binary Neural Networks Seitaro Koyama, Toshimichi Saito (HU)  MBE2019-39 NC2019-30 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | The 3-layer dynamic binary neural networks (3-DBNNs) are characterized by ternary connection parameters and signum activation function. Depending on the connection parameters, the 3-DBNN can generate various binary periodic orbits. The 3-DBNN is based on the 2-layer DBNN discussed in our previous publications. Applications include associative memories and central pattern generators. In this paper, we analyze the dynamics of the 3-DBNN that generates a target binary periodic orbit. In order to analyze the dynamics, we introduce two feature quantities. The first quantity characterizes stability of the target periodic orbit. The second quantity characterizes sparsity of the connection. We consider relationship between stability of the target periodic orbit and sparsity of the connection. We can see that as the connection sparsity increases, the orbit stability tends to be strong. As the connection sparsity increases further, the orbit stability becomes weak. |
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| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | Dynamic binary neural networks / Associative memories / Periodic orbits / Stability / / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 119, no. 225, NC2019-30, pp. 51-51, Oct. 2019. | |
| Paper # | NC2019-30 | |
| Date of Issue | 2019-10-04 (MBE, NC) | |
| ISSN | Online edition: ISSN 2432-6380 | |
| Copyright and reproduction |
All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034) | |
| Download PDF | MBE2019-39 NC2019-30 |
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| Conference Information | |
| Committee | MBE NC |
| Conference Date | 2019-10-11 - 2019-10-12 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | |
| Paper Information | |
| Registration To | NC |
| Conference Code | 2019-10-MBE-NC |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Stability of Periodic Orbits in 3-Layer Dynamic Binary Neural Networks |
| Sub Title (in English) | |
| Keyword(1) | Dynamic binary neural networks |
| Keyword(2) | Associative memories |
| Keyword(3) | Periodic orbits |
| Keyword(4) | Stability |
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| 1st Author's Name | Seitaro Koyama |
| 1st Author's Affiliation | Hosei University (HU) |
| 2nd Author's Name | Toshimichi Saito |
| 2nd Author's Affiliation | Hosei University (HU) |
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| Speaker | Author-1 |
| Date Time | 2019-10-12 10:00:00 |
| Presentation Time | 25 minutes |
| Registration for | NC |
| Paper # | MBE2019-39, NC2019-30 |
| Volume (vol) | vol.119 |
| Number (no) | no.224(MBE), no.225(NC) |
| Page | p.51 |
| #Pages | 1 |
| Date of Issue | 2019-10-04 (MBE, NC) |
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