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Paper Abstract and Keywords
Presentation 2016-07-22 09:25
A Novel Modulation Classification Method in Cognitive Radios using Deep Network
Xu Zhu, Takeo Fujii (UEC) SR2016-50
Abstract (in Japanese) (See Japanese page) 
(in English) This paper proposes a universal modulation classification method based on Denoise Stacked Sparse Auto-encoder (DSSA), one type of deep networks, which extracts features and classifies for single carrier modulation classification. This method can extract modulation features automatically, and classify input signals based on the features it extracted, which enables us to utilize it on as many modulations as we use in practice. Same as conventional neural network, a labeled samples base is necessary for parameters training. Network structure, however, is different for conventional neural network, since it can simplify an exponentially large number of hidden units by a multi-layer construction. This simplification enables us to achieve better back propagation and network tune. In addition, Denoising Auto-encoder extends the performance of Auto-encoder by reconstruct the data from a corrupted version to extract more robust feature. A series of results of binary classification, along with multi-classes classification are given by simulation, which shows an more universal utilization than other methods.
Keyword (in Japanese) (See Japanese page) 
(in English) modulation classification / cognitive radio / denoising autoencoder / / / / /  
Reference Info. IEICE Tech. Rep., vol. 116, no. 148, SR2016-50, pp. 103-106, July 2016.
Paper # SR2016-50 
Date of Issue 2016-07-13 (SR) 
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 SR2016-50

Conference Information
Committee RCS RCC ASN NS SR  
Conference Date 2016-07-20 - 2016-07-22 
Place (in Japanese) (See Japanese page) 
Place (in English)  
Topics (in Japanese) (See Japanese page) 
Topics (in English) Wireless Distributed Network, M2M: Machine-to-Machine, D2D (Device-to-Device)，etc. 
Paper Information
Registration To SR 
Conference Code 2016-07-RCS-RCC-ASN-NS-SR 
Language English 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) A Novel Modulation Classification Method in Cognitive Radios using Deep Network 
Sub Title (in English)  
Keyword(1) modulation classification  
Keyword(2) cognitive radio  
Keyword(3) denoising autoencoder  
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1st Author's Name Xu Zhu  
1st Author's Affiliation The University of Electro-Communications (UEC)
2nd Author's Name Takeo Fujii  
2nd Author's Affiliation The University of Electro-Communications (UEC)
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Speaker Author-1 
Date Time 2016-07-22 09:25:00 
Presentation Time 25 minutes 
Registration for SR 
Paper # SR2016-50 
Volume (vol) vol.116 
Number (no) no.148 
Page pp.103-106 
#Pages 4 
Date of Issue 2016-07-13 (SR) 

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