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Paper Abstract and Keywords
Presentation 2017-05-26 14:15
Frequency Filter Networks on EEG Data for Emotion Analysis
Miku Yanagimoto, Chika Sugimoto, Tomoharu Nagao (YNU) NC2017-4
Abstract (in Japanese) (See Japanese page) 
(in English) In EEG-based emotion recognition (EEG-ER), enhancing feature extractors is often difficult.
In such cases, the use of deep neural networks which are capable of classification and recognition by the input of raw data is desirable.
Therefore, effective components and models of neural networks for EEG-based recognition must be proposed.
This paper proposes a discrete Fourier transform (DFT) layer, inverse DFT (IDFT) layer, and other components to compose a frequency filter module.
This module was proposed for embedding a bandpass filter suitable for EEG data and the targets.
The proposed models were compared with their counterparts and state-of-the-art models, and evaluated according to their accuracies for emotion recognition.
The results showed that the frequency filter module is effective in preprocessing or interpreting some features in EEG with a characteristic in frequency domain.
Keyword (in Japanese) (See Japanese page) 
(in English) neural networks / deep learning / Fourier transform / EEG / emotions / / /  
Reference Info. IEICE Tech. Rep., vol. 117, no. 64, NC2017-4, pp. 19-24, May 2017.
Paper # NC2017-4 
Date of Issue 2017-05-19 (NC) 
ISSN Print edition: ISSN 0913-5685    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 NC2017-4

Conference Information
Committee MBE NC  
Conference Date 2017-05-26 - 2017-05-26 
Place (in Japanese) (See Japanese page) 
Place (in English) Toyama Prefectural Univ. 
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To NC 
Conference Code 2017-05-MBE-NC 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Frequency Filter Networks on EEG Data for Emotion Analysis 
Sub Title (in English)  
Keyword(1) neural networks  
Keyword(2) deep learning  
Keyword(3) Fourier transform  
Keyword(4) EEG  
Keyword(5) emotions  
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1st Author's Name Miku Yanagimoto  
1st Author's Affiliation Yokohama National University (YNU)
2nd Author's Name Chika Sugimoto  
2nd Author's Affiliation Yokohama National University (YNU)
3rd Author's Name Tomoharu Nagao  
3rd Author's Affiliation Yokohama National University (YNU)
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Speaker Author-1 
Date Time 2017-05-26 14:15:00 
Presentation Time 25 minutes 
Registration for NC 
Paper # NC2017-4 
Volume (vol) vol.117 
Number (no) no.64 
Page pp.19-24 
#Pages
Date of Issue 2017-05-19 (NC) 


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