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Paper Abstract and Keywords
Presentation 2021-03-05 16:55
Electromagnetic Noise Classification and Novelty Detection for Frequency Sharing among Various Communications in the Manufacturing Field
Michio Miyamoto, Ayano Ohnishi, Yoshio Takeuchi (ATR), Toshiyuki Maeyama (ATR/Takushoku Univ.), Akio Hasegawa, Hiroyuki Yokoyama (ATR) SR2020-89
Abstract (in Japanese) (See Japanese page) 
(in English) Machine learning is applied to classify the electromagnetic noise generated in the manufacturing field. The frequency and pattern of electromagnetic noise generated in the manufacturing field depends on the source equipment. Therefore, there is a problem that a new noise pattern that occurs infrequently and has not been learned is erroneously classified as a known pattern. Machine learning novelty detection can be used to find unknown patterns. However, when operating measurement, many computer resources are required to operate classification and novelty detection in parallel. In this report, we describe a method for detecting unlearned patterns using the predict probability of classification estimation results by supervised machine learning.
Keyword (in Japanese) (See Japanese page) 
(in English) Factory Wireless Communication / Electromagnetic Noise / Machine Learning Classification / Novelty Detection / / / /  
Reference Info. IEICE Tech. Rep., vol. 120, no. 405, SR2020-89, pp. 99-103, March 2021.
Paper # SR2020-89 
Date of Issue 2021-02-24 (SR) 
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 SR2020-89

Conference Information
Committee RCS SR SRW  
Conference Date 2021-03-03 - 2021-03-05 
Place (in Japanese) (See Japanese page) 
Place (in English) Online 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Mobile Communication Workshop 
Paper Information
Registration To SR 
Conference Code 2021-03-RCS-SR-SRW 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Electromagnetic Noise Classification and Novelty Detection for Frequency Sharing among Various Communications in the Manufacturing Field 
Sub Title (in English)  
Keyword(1) Factory Wireless Communication  
Keyword(2) Electromagnetic Noise  
Keyword(3) Machine Learning Classification  
Keyword(4) Novelty Detection  
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1st Author's Name Michio Miyamoto  
1st Author's Affiliation Advanced Telecommunications Research Institute International (ATR)
2nd Author's Name Ayano Ohnishi  
2nd Author's Affiliation Advanced Telecommunications Research Institute International (ATR)
3rd Author's Name Yoshio Takeuchi  
3rd Author's Affiliation Advanced Telecommunications Research Institute International (ATR)
4th Author's Name Toshiyuki Maeyama  
4th Author's Affiliation Advanced Telecommunications Research Institute International/Takushoku University (ATR/Takushoku Univ.)
5th Author's Name Akio Hasegawa  
5th Author's Affiliation Advanced Telecommunications Research Institute International (ATR)
6th Author's Name Hiroyuki Yokoyama  
6th Author's Affiliation Advanced Telecommunications Research Institute International (ATR)
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Speaker Author-1 
Date Time 2021-03-05 16:55:00 
Presentation Time 25 minutes 
Registration for SR 
Paper # SR2020-89 
Volume (vol) vol.120 
Number (no) no.405 
Page pp.99-103 
#Pages 5 
Date of Issue 2021-02-24 (SR) 

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