Paper Abstract and Keywords |
Presentation |
2019-07-04 09:15
A Study of Parameter Control Method Based on QoE by Machine learning Hiroto Kurosawa, Takuya Shindou, Takefumi Hiraguri (NIT) CS2019-26 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
In recent years, machine learning such as deep learning has attracted attention. Various applications have been proposed and studied in the wireless communication field. Therefore, in the objective communication quality estimation, we consider a method that uses evaluation parameters specific to wireless communication such as propagation error, interference, transmission, throughput, packet loss, etc. for machine learning. In this paper, we focus especially on weight adjustment of neural networks. Conventionally, error back-propagation method etc. are used to adjust this weight, but the performance when using stochastic optimization method is confirmed. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
Deep Learning / Differential Evolution / QoE / Machine Learning / / / / |
Reference Info. |
IEICE Tech. Rep., vol. 119, no. 101, CS2019-26, pp. 55-56, July 2019. |
Paper # |
CS2019-26 |
Date of Issue |
2019-06-27 (CS) |
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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CS2019-26 |
Conference Information |
Committee |
CS |
Conference Date |
2019-07-04 - 2019-07-05 |
Place (in Japanese) |
(See Japanese page) |
Place (in English) |
Amami City Social Welfare Center |
Topics (in Japanese) |
(See Japanese page) |
Topics (in English) |
Next Generation Networks, Access Networks, Broadband Access, Power Line Communications, Wireless Communication Systems, Coding Systems, etc. |
Paper Information |
Registration To |
CS |
Conference Code |
2019-07-CS |
Language |
Japanese |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
A Study of Parameter Control Method Based on QoE by Machine learning |
Sub Title (in English) |
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Keyword(1) |
Deep Learning |
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Differential Evolution |
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QoE |
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Machine Learning |
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1st Author's Name |
Hiroto Kurosawa |
1st Author's Affiliation |
Nippon Institute of Technology (NIT) |
2nd Author's Name |
Takuya Shindou |
2nd Author's Affiliation |
Nippon Institute of Technology (NIT) |
3rd Author's Name |
Takefumi Hiraguri |
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Nippon Institute of Technology (NIT) |
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Speaker |
Author-1 |
Date Time |
2019-07-04 09:15:00 |
Presentation Time |
15 minutes |
Registration for |
CS |
Paper # |
CS2019-26 |
Volume (vol) |
vol.119 |
Number (no) |
no.101 |
Page |
pp.55-56 |
#Pages |
2 |
Date of Issue |
2019-06-27 (CS) |
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