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| Presentation | 2014-06-30 16:00 Backpropagation learning using inverse function delay-less model Yuta Horiuchi (Tohoku Univ.), Yoshihiro Hayakawa (SNCT), Takeshi Onomi, Koji Nakajima (Tohoku Univ.)  NLP2014-25 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | The Inverse function Delayed (ID) model has been proposed as one of novel neural models. ID model has a oscillation capacity. This model can solve some local minimum problem in combinatorial optimization problems. However, The drawback of the ID model is large calculation cost. So it is difficult to apply for large size combinational optimization problems. This problem was solved by Inverse function Delay-Less (IDL) model in com- binational optimization problems. We had derived back propagation learning with IDL model at continuous-time. However, the most popular BP learn in discrete-time. So this study is to build discrete-time IDL model BP learning. | |
| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | Neural network / Hierarchical network / Inverse function / Back propagation learning / / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 114, no. 113, NLP2014-25, pp. 27-30, June 2014. | |
| Paper # | NLP2014-25 | |
| Date of Issue | 2014-06-23 (NLP) | |
| 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 | NLP2014-25 |
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| Conference Information | |
| Committee | NLP |
| Conference Date | 2014-06-30 - 2014-07-01 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Tohoku Univ. |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | Nonlinear Problems, etc. |
| Paper Information | |
| Registration To | NLP |
| Conference Code | 2014-06-NLP |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Backpropagation learning using inverse function delay-less model |
| Sub Title (in English) | |
| Keyword(1) | Neural network |
| Keyword(2) | Hierarchical network |
| Keyword(3) | Inverse function |
| Keyword(4) | Back propagation learning |
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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 | 2014-06-30 16:00:00 |
| Presentation Time | 25 minutes |
| Registration for | NLP |
| Paper # | NLP2014-25 |
| Volume (vol) | vol.114 |
| Number (no) | no.113 |
| Page | pp.27-30 |
| #Pages | 4 |
| Date of Issue | 2014-06-23 (NLP) |
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