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| Presentation | 2020-12-10 15:35 Automatic Structural Adjustment Method of Microstrip BPF using Deep Q-network Kohei Takano, Masataka Ohira, Zhewang Ma (Saitama Univ.)  MW2020-76 Link to ES Tech. Rep. Archives: MW2020-76 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | The design of bandpass filter (BPF), especially its structural adjustment, is often performed by trial and error with human experience and intuition. Optimization and machine learning are being investigated to automate the design process. Among them, mechanical structural adjustment has been reported for BPF design using deep Q network (DQN), which is a neural network (NN) used for reinforcement learning. However, these methods are mainly employed for cavity filters. No examples on the application to planar BPF, of which cross couplings are difficult to control, have been reported yet. In this paper, we propose an automatic structural adjustment method of microstrip BPF using DQN. In the proposed method, it is possible to learn a design process from various initial structural parameters at high speed by using both a forward model that can calculate the frequency characteristics instantly and an inverse model that calculates initial values of structural parameters. As an example, a DQN for automatic structural adjustment of the fifth-order microstrip BPF is constructed. The effectiveness is demonstrated through the evaluation of versatility of the constructed DQN. | |
| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | Bandpass filter / Deep Q-network / Reinforcement learning / Automatic design / / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 120, no. 280, MW2020-76, pp. 30-35, Dec. 2020. | |
| Paper # | MW2020-76 | |
| Date of Issue | 2020-12-03 (MW) | |
| 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 | MW2020-76 Link to ES Tech. Rep. Archives: MW2020-76 |
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| Conference Information | |
| Committee | MW |
| Conference Date | 2020-12-10 - 2020-12-10 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | |
| Paper Information | |
| Registration To | MW |
| Conference Code | 2020-12-MW |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Automatic Structural Adjustment Method of Microstrip BPF using Deep Q-network |
| Sub Title (in English) | |
| Keyword(1) | Bandpass filter |
| Keyword(2) | Deep Q-network |
| Keyword(3) | Reinforcement learning |
| Keyword(4) | Automatic design |
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| 1st Author's Name | Kohei Takano |
| 1st Author's Affiliation | Saitama University (Saitama Univ.) |
| 2nd Author's Name | Masataka Ohira |
| 2nd Author's Affiliation | Saitama University (Saitama Univ.) |
| 3rd Author's Name | Zhewang Ma |
| 3rd Author's Affiliation | Saitama University (Saitama Univ.) |
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| Speaker | Author-1 |
| Date Time | 2020-12-10 15:35:00 |
| Presentation Time | 25 minutes |
| Registration for | MW |
| Paper # | MW2020-76 |
| Volume (vol) | vol.120 |
| Number (no) | no.280 |
| Page | pp.30-35 |
| #Pages | 6 |
| Date of Issue | 2020-12-03 (MW) |
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