| Paper Abstract and Keywords |
| Presentation |
2025-10-03 11:40
Multiple fixed points and stability in majority binary neural networks Moeka Yokose, Ryota Toyama, Toshimichi Saito (HU) CAS2025-34 NLP2025-51 |
| Abstract |
(in Japanese) |
(See Japanese page) |
| (in English) |
The majority binary neural network consists of simple majority neurons from three binary inputs to one binary output.
The dynamics is described by an autonomous difference equation.
As the connections vary, the network can have various fixed points and periodic orbits.
The fixed points and periodic orbits can co-exisit and the network exhibits one of them depending on the initial condition.
This paper analyzes the multiple fixed points using simple feature quantities that evaluate the number and stability of fixed points.
Performing numerical analysis for typical networks, we have clarified that the number and stability vary complicatedly.
Especially, we have discovered multiple fixed points with the strongest stability.
The results will be developed into applications including associative memories and clustering methods for binary data sets. |
| Keyword |
(in Japanese) |
(See Japanese page) |
| (in English) |
binary neural networks / majority neurons / stability / / / / / |
| Reference Info. |
IEICE Tech. Rep., vol. 125, no. 190, NLP2025-51, pp. 82-85, Oct. 2025. |
| Paper # |
NLP2025-51 |
| Date of Issue |
2025-09-25 (CAS, NLP) |
| 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 |
CAS2025-34 NLP2025-51 |
| Conference Information |
| Committee |
CAS NLP |
| Conference Date |
2025-10-02 - 2025-10-03 |
| Place (in Japanese) |
(See Japanese page) |
| Place (in English) |
|
| Topics (in Japanese) |
(See Japanese page) |
| Topics (in English) |
Nonlinear Problems, Circuits and Systems, etc. |
| Paper Information |
| Registration To |
NLP |
| Conference Code |
2025-10-CAS-NLP |
| Language |
Japanese |
| Title (in Japanese) |
(See Japanese page) |
| Sub Title (in Japanese) |
(See Japanese page) |
| Title (in English) |
Multiple fixed points and stability in majority binary neural networks |
| Sub Title (in English) |
|
| Keyword(1) |
binary neural networks |
| Keyword(2) |
majority neurons |
| Keyword(3) |
stability |
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| 1st Author's Name |
Moeka Yokose |
| 1st Author's Affiliation |
Hosei University (HU) |
| 2nd Author's Name |
Ryota Toyama |
| 2nd Author's Affiliation |
Hosei University (HU) |
| 3rd Author's Name |
Toshimichi Saito |
| 3rd Author's Affiliation |
Hosei University (HU) |
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| Speaker |
Author-1 |
| Date Time |
2025-10-03 11:40:00 |
| Presentation Time |
25 minutes |
| Registration for |
NLP |
| Paper # |
CAS2025-34, NLP2025-51 |
| Volume (vol) |
vol.125 |
| Number (no) |
no.189(CAS), no.190(NLP) |
| Page |
pp.82-85 |
| #Pages |
4 |
| Date of Issue |
2025-09-25 (CAS, NLP) |