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| Presentation | 2013-01-29 12:00 Multi-layered GMDH-type neural network algorithm using Prediction Sum of Squares (PSS) criterion and Its application to nonlinear system identification Tadashi Kondo, Junji Ueno, Shoichiro Takao (Tokushima Univ.)  KBSE2012-64 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | In this study, a revised Group Method of Data Handling (GMDH)-type neural network using Prediction Sum of Squares (PSS) criterion is proposed and applied to the identification problem of the nonlinear system. Revised GMDH-type neural network algorithm can organize the neural network architectures using the heuristic self-organization method which is a kind of evolutional computation. It has an ability of self-selecting optimum neural network architecture from three neural network architectures such as sigmoid function neural network, radial basis function (RBF) neural network and polynomial neural network and also has abilities of self-selecting the number of layers, the number of neurons in hidden layers and useful input variables so as to minimize PSS criterion. Furthermore, in this algorithm, the principal component-regression analysis is used to learning calculation of the weights and there is no multi co-linearity in the neural network architectures. This algorithm is applied to the nonlinear system identification problem and it is shown that this algorithm is accurate and useful for the nonlinear system identification. | |
| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | GMDH / Neural network / Nonlinear system identification / / / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 112, no. 419, KBSE2012-64, pp. 35-40, Jan. 2013. | |
| Paper # | KBSE2012-64 | |
| Date of Issue | 2013-01-21 (KBSE) | |
| 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 | KBSE2012-64 |
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| Conference Information | |
| Committee | KBSE |
| Conference Date | 2013-01-28 - 2013-01-29 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Kikai-Shinko-Kaikan Bldg |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | General session |
| Paper Information | |
| Registration To | KBSE |
| Conference Code | 2013-01-KBSE |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Multi-layered GMDH-type neural network algorithm using Prediction Sum of Squares (PSS) criterion and Its application to nonlinear system identification |
| Sub Title (in English) | |
| Keyword(1) | GMDH |
| Keyword(2) | Neural network |
| Keyword(3) | Nonlinear system identification |
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| 1st Author's Name | Tadashi Kondo |
| 1st Author's Affiliation | The University of Tokushima (Tokushima Univ.) |
| 2nd Author's Name | Junji Ueno |
| 2nd Author's Affiliation | The University of Tokushima (Tokushima Univ.) |
| 3rd Author's Name | Shoichiro Takao |
| 3rd Author's Affiliation | The University of Tokushima (Tokushima Univ.) |
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| Speaker | Author-1 |
| Date Time | 2013-01-29 12:00:00 |
| Presentation Time | 30 minutes |
| Registration for | KBSE |
| Paper # | KBSE2012-64 |
| Volume (vol) | vol.112 |
| Number (no) | no.419 |
| Page | pp.35-40 |
| #Pages | 6 |
| Date of Issue | 2013-01-21 (KBSE) |
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