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| Presentation | 2022-03-03 11:10 Basic characteristics of SAM spiking neuron model with rate coding Minoru Motoki (Kumamoto KOSEN)  NC2021-63 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | he SAM neuron model is one of spiking neural networks that have high computational efficiency and familiarity for digital circuitry because of only 1 bit information expression as edge trainable AI device. The SAM neuron model has 1 more parameters than the LIF neuron model. The SAM neuron model has an advantage that it maintains a more accurate correspondence between the continuous and discrete representations, avoiding a reduction in the frequency of output spikes even if the sampling interval is wide. This paper describes a basic characteristics of the SAM neuron model with rate coding. Moreover, we show that the 2-2-1 multilayer SAM spiking neural network can express XOR task with the same number of neurons as the sigmoid type artificial neuron of the multilayer neural network. | |
| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | Spiking Neuron / SAM neuron model / LIF neuron model / rate coding / / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 121, no. 390, NC2021-63, pp. 88-93, March 2022. | |
| Paper # | NC2021-63 | |
| Date of Issue | 2022-02-23 (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 | NC2021-63 |
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| Conference Information | |
| Committee | MBE NC |
| Conference Date | 2022-03-02 - 2022-03-04 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Online |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | |
| Paper Information | |
| Registration To | NC |
| Conference Code | 2022-03-MBE-NC |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Basic characteristics of SAM spiking neuron model with rate coding |
| Sub Title (in English) | |
| Keyword(1) | Spiking Neuron |
| Keyword(2) | SAM neuron model |
| Keyword(3) | LIF neuron model |
| Keyword(4) | rate coding |
| Keyword(5) | |
| Keyword(6) | |
| Keyword(7) | |
| Keyword(8) | |
| 1st Author's Name | Minoru Motoki |
| 1st Author's Affiliation | National Institute of Technology, Kumamoto College (Kumamoto KOSEN) |
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| Speaker | Author-1 |
| Date Time | 2022-03-03 11:10:00 |
| Presentation Time | 25 minutes |
| Registration for | NC |
| Paper # | NC2021-63 |
| Volume (vol) | vol.121 |
| Number (no) | no.390 |
| Page | pp.88-93 |
| #Pages | 6 |
| Date of Issue | 2022-02-23 (NC) |
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