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| Presentation | 2022-08-29 10:20 Compensation Performance of DNN-based Nonlinear Equalizer for Optical Communication Systems Jinya Nakamura, Kai Ikuta, Daisuke Motai, Moriya Nakamura (Meiji Univ.)  PN2022-10 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | We investigated and compared the performances of three-layer-ANN- and four-layer-DNN-based nonlinear equalizers used for the compensation of optical nonlinear distortion. We confirmed that the learning speed of DNN was faster than that of ANN when we optimized the learning rate. However, the learning process of the DNN-based nonlinear equalizer was unstable and diverged in some cases. We clarified that the divergence of the learning was caused by the local-minimum trapping where the weights became extremely large and noise is clipped by the saturation characteristics of the DNN units. Furthermore, we confirmed that the divergence can be suppressed by using L2 regularization. When the compensation accuracies of the ANN and DNN were compared based on computational complexity, no significant difference was observed. | |
| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | optical nonlinear compensation / nonlinear equalizer / deep neural network / regularization / / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 122, no. 169, PN2022-10, pp. 10-14, Aug. 2022. | |
| Paper # | PN2022-10 | |
| Date of Issue | 2022-08-22 (PN) | |
| ISSN | 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 | PN2022-10 |
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| Conference Information | |
| Committee | PN |
| Conference Date | 2022-08-29 - 2022-08-30 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | |
| Paper Information | |
| Registration To | PN |
| Conference Code | 2022-08-PN |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Compensation Performance of DNN-based Nonlinear Equalizer for Optical Communication Systems |
| Sub Title (in English) | |
| Keyword(1) | optical nonlinear compensation |
| Keyword(2) | nonlinear equalizer |
| Keyword(3) | deep neural network |
| Keyword(4) | regularization |
| Keyword(5) | |
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| 1st Author's Name | Jinya Nakamura |
| 1st Author's Affiliation | Meiji University (Meiji Univ.) |
| 2nd Author's Name | Kai Ikuta |
| 2nd Author's Affiliation | Meiji University (Meiji Univ.) |
| 3rd Author's Name | Daisuke Motai |
| 3rd Author's Affiliation | Meiji University (Meiji Univ.) |
| 4th Author's Name | Moriya Nakamura |
| 4th Author's Affiliation | Meiji University (Meiji Univ.) |
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| Speaker | Author-1 |
| Date Time | 2022-08-29 10:20:00 |
| Presentation Time | 25 minutes |
| Registration for | PN |
| Paper # | PN2022-10 |
| Volume (vol) | vol.122 |
| Number (no) | no.169 |
| Page | pp.10-14 |
| #Pages | 5 |
| Date of Issue | 2022-08-22 (PN) |
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