Paper Abstract and Keywords |
Presentation |
2020-03-06 11:10
The Analysis of Associative Memory with Discrete Synapses Ryuta Sasaki, Toru Aonishi (Tokyo Tech) NC2019-108 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
Recently, as the increasing needs of the development of high-speed Ising computing specific hardware, it has been required to evaluate the change of its calculation accuracy due to hardware implementation with physically limited resources. For instance, in digital hardware such as field-programmable gate arrays, as reducing the number of bits representing connection values, the density of integrated Ising spins and the speed of computing become higher while the calculation accuracy becomes lower. To optimize the accuracy-efficacy trade-off, we have to estimate the change in the performance of the Ising computing machine depending on the number of bits representing connection values. In this study, to achieve this issue, we focus on the Hopfield model with discrete synapses, which is one of the canonical Ising computing models. Previous studies had analyzed the effect of a few nonlinear functions (e.g. sign) for mapping connection values on the Hopfield model with statistical mechanics methods, but had not evaluated the effect of discretization for connection values in detail. We derived the order parameter equations of the Hopfield model with discrete synapses using the replica method, and clarified the relationship between the number of bits representing connection values and the critical memory capacity. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
statistical mechanics / Hopfield model / replica method / critical memory capacity / phase transitions / / / |
Reference Info. |
IEICE Tech. Rep., vol. 119, no. 453, NC2019-108, pp. 187-192, March 2020. |
Paper # |
NC2019-108 |
Date of Issue |
2020-02-26 (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) |
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NC2019-108 |
Conference Information |
Committee |
NC MBE |
Conference Date |
2020-03-04 - 2020-03-06 |
Place (in Japanese) |
(See Japanese page) |
Place (in English) |
University of Electro Communications |
Topics (in Japanese) |
(See Japanese page) |
Topics (in English) |
Neuro Computing, Medical Engineering, etc. |
Paper Information |
Registration To |
NC |
Conference Code |
2020-03-NC-MBE |
Language |
Japanese |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
The Analysis of Associative Memory with Discrete Synapses |
Sub Title (in English) |
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statistical mechanics |
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Hopfield model |
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replica method |
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critical memory capacity |
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phase transitions |
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1st Author's Name |
Ryuta Sasaki |
1st Author's Affiliation |
Tokyo Institute of Technology (Tokyo Tech) |
2nd Author's Name |
Toru Aonishi |
2nd Author's Affiliation |
Tokyo Institute of Technology (Tokyo Tech) |
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Speaker |
Author-1 |
Date Time |
2020-03-06 11:10:00 |
Presentation Time |
25 minutes |
Registration for |
NC |
Paper # |
NC2019-108 |
Volume (vol) |
vol.119 |
Number (no) |
no.453 |
Page |
pp.187-192 |
#Pages |
6 |
Date of Issue |
2020-02-26 (NC) |
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