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Paper Abstract and Keywords
Presentation 2014-11-21 11:00
A Comparison of Back Propagation Learning between the Inverse-function Delayless Model and a Conventional Model
Yuta Horiuchi (Tohoku Univ), Yoshihiro Hayakawa (SNCT), Takeshi Onomi, Koji Nakajima (Tohoku Univ) NC2014-26
Abstract (in Japanese) (See Japanese page) 
(in English) For the combinatorial optimization problem using the hopfield model, avoidance of the local minimum problem is important. It is improved by suggestion of the Inverse function Delay model (ID model) and the Inverse function Delayless model (IDL model). On the other hand, the backpropagation (BP) learning has a local minimum problem like a combinatorial optimization problem. We studied the BP learning using the IDL model, and we showed that learning performance improved by introducing the velocity amplitude function in the IDL model into a learning equation. However, it does not understand why performance improves. We investigates the factor of the enhancement of learning performance by introducing a velocity amplitude function.
Keyword (in Japanese) (See Japanese page) 
(in English) Neural Network / Hierarchical network / Back Propagation / / / / /  
Reference Info. IEICE Tech. Rep., vol. 114, no. 326, NC2014-26, pp. 7-10, Nov. 2014.
Paper # NC2014-26 
Date of Issue 2014-11-14 (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 NC2014-26

Conference Information
Committee MBE NC  
Conference Date 2014-11-21 - 2014-11-22 
Place (in Japanese) (See Japanese page) 
Place (in English) Tohoku University 
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To NC 
Conference Code 2014-11-MBE-NC 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) A Comparison of Back Propagation Learning between the Inverse-function Delayless Model and a Conventional Model 
Sub Title (in English)  
Keyword(1) Neural Network  
Keyword(2) Hierarchical network  
Keyword(3) Back Propagation  
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1st Author's Name Yuta Horiuchi  
1st Author's Affiliation Tohoku University (Tohoku Univ)
2nd Author's Name Yoshihiro Hayakawa  
2nd Author's Affiliation Sendai National College of Technology (SNCT)
3rd Author's Name Takeshi Onomi  
3rd Author's Affiliation Tohoku University (Tohoku Univ)
4th Author's Name Koji Nakajima  
4th Author's Affiliation Tohoku University (Tohoku Univ)
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Speaker Author-1 
Date Time 2014-11-21 11:00:00 
Presentation Time 25 minutes 
Registration for NC 
Paper # NC2014-26 
Volume (vol) vol.114 
Number (no) no.326 
Page pp.7-10 
#Pages 4 
Date of Issue 2014-11-14 (NC) 

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