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| Presentation | 2010-12-19 11:45 Limited General Regression Neural Networks Koichiro Yamauchi (Chubu Univ.)  MBE2010-71 NC2010-82 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | An incremental learning method for the general regression neural network(GRNN) for embedded systems is proposed. Although the GRNN learns new samples by allocating new hidden units, the hidden unit number is limited to an upper bound. Therefore, if the number of hidden units reaches to the upper bound, the GRNN has to remove one redundant hidden unit to learn a new sample. To find the redundant hidden unit, the proposed one measures a ratio of redundancy of each hidden unit using a Kernel technique. Using this method, the GRNN basically substitutes the duty of the most redundant hidden unit using the remaining hidden units. Moreover, the proposed one reduces the magniturd of interference due to the leanring. Experimental results shows that the method successfully reduces the error even if the number of hidden units is limited to a certain upper bound. |
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| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | Limited General Regression Neural Networks / Kernel Machine / Approximated Linear Dependency (ALD) / Incremental Learning / / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 110, no. 355, NC2010-82, pp. 91-96, Dec. 2010. | |
| Paper # | NC2010-82 | |
| Date of Issue | 2010-12-12 (MBE, 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 | MBE2010-71 NC2010-82 |
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| Conference Information | |
| Committee | NC MBE |
| Conference Date | 2010-12-19 - 2010-12-19 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Nagoya Univ. |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | |
| Paper Information | |
| Registration To | NC |
| Conference Code | 2010-12-NC-MBE |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Limited General Regression Neural Networks |
| Sub Title (in English) | |
| Keyword(1) | Limited General Regression Neural Networks |
| Keyword(2) | Kernel Machine |
| Keyword(3) | Approximated Linear Dependency (ALD) |
| Keyword(4) | Incremental Learning |
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| 1st Author's Name | Koichiro Yamauchi |
| 1st Author's Affiliation | Chubu University (Chubu Univ.) |
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| Speaker | Author-1 |
| Date Time | 2010-12-19 11:45:00 |
| Presentation Time | 25 minutes |
| Registration for | NC |
| Paper # | MBE2010-71, NC2010-82 |
| Volume (vol) | vol.110 |
| Number (no) | no.354(MBE), no.355(NC) |
| Page | pp.91-96 |
| #Pages | 6 |
| Date of Issue | 2010-12-12 (MBE, NC) |
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