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Paper Abstract and Keywords
Presentation 2011-03-07 11:30
Maximum Power Point Tracking Converter Using a Limited General Regression Neural Network
Koichiro Yamauchi (Chubu Univ) NC2010-134
Abstract (in Japanese) (See Japanese page) 
(in English) In this paper, we propose a limited general regression neural network (LGRNN) for embedded systems.
The LGRNN is an improved version of general regression neural network that continues incremental learning under a fixed number of hidden units.

Initially, the LGRNN learns new samples incrementally by allocating new hidden units.
If the number of hidden units reaches the upper bound, the LGRNN has to remove one useless hidden unit to learn a new sample.
However, there are cases in which the adverse effects of removing a useless unit are greater than the positive effects of learning the new sample.
In this case, the LGRNN should refrain from learning the new sample.
To achieve this, the LGRNN predicts the effects of several learning options (e.g., ignore or learning) before the learning process begins, and chooses the best learning option to be executed.
Keyword (in Japanese) (See Japanese page) 
(in English) imited General Regression Neural Networks / Kernel Machine / pproximated Linear Dependency / Incremental Learning / Maximum Power Point Tracking (MPPT) / / /  
Reference Info. IEICE Tech. Rep., vol. 110, no. 461, NC2010-134, pp. 41-46, March 2011.
Paper # NC2010-134 
Date of Issue 2011-02-28 (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 NC2010-134

Conference Information
Committee NC MBE  
Conference Date 2011-03-07 - 2011-03-09 
Place (in Japanese) (See Japanese page) 
Place (in English) Tamagawa University 
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To NC 
Conference Code 2011-03-NC-MBE 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Maximum Power Point Tracking Converter Using a Limited General Regression Neural Network 
Sub Title (in English)  
Keyword(1) imited General Regression Neural Networks  
Keyword(2) Kernel Machine  
Keyword(3) pproximated Linear Dependency  
Keyword(4) Incremental Learning  
Keyword(5) Maximum Power Point Tracking (MPPT)  
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1st Author's Name Koichiro Yamauchi  
1st Author's Affiliation Chubu University (Chubu Univ)
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Speaker
Date Time 2011-03-07 11:30:00 
Presentation Time 25 
Registration for NC 
Paper # IEICE-NC2010-134 
Volume (vol) IEICE-110 
Number (no) no.461 
Page pp.41-46 
#Pages IEICE-6 
Date of Issue IEICE-NC-2011-02-28 


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