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Hokkaido University Collection of Scholarly and Academic Papers >
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Modal amplitude and phase estimation of multimode near field patterns based on artificial neural network with the help of grey-wolf-optimizer
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| Title: | Modal amplitude and phase estimation of multimode near field patterns based on artificial neural network with the help of grey-wolf-optimizer |
| Authors: | Sugawara, Naoto Browse this author | | Fujisawa, Takeshi Browse this author →KAKEN DB | | Nakamura, Kodai Browse this author | | Sawada, Yusuke Browse this author | | Mori, Takayoshi Browse this author | | Sakamoto, Taiji Browse this author | | Imada, Ryota Browse this author | | Matsui, Takashi Browse this author | | Nakajima, Kazuhide Browse this author | | Saitoh, Kunimasa Browse this author →KAKEN DB |
| Keywords: | Modal decomposition technique | | Artificial neural network | | Mode division multiplexing | | Mode scrambler |
| Issue Date: | Dec-2021 |
| Publisher: | Elsevier |
| Journal Title: | Optical fiber technology |
| Volume: | 67 |
| Start Page: | 102720 |
| Publisher DOI: | 10.1016/j.yofte.2021.102720 |
| Abstract: | A simple and efficient method for estimating modal amplitude and phase of multimode near field patterns (NFPs) based on artificial-neural-network (ANN) with the help of the optimization method is proposed. The inferred amplitude and phase of measured NFPs based on ANN are refined by using a grey-wolf optimizer (GWO). By using the proposed method, the image correlation between reproduced and measured NFPs is improved without re-training of ANN, which is the most time-consuming part of ANN-based numerical modal decomposition technique. Numerical examples of three and six mode cases are presented for the estimation using simple ANN. For six-mode case, the correlation is greatly improved by using the optimizer. Finally, the estimation of the measured NFPs from three-mode exchanger and six-mode mode conversion grating is implemented, and 5% improvement in the correlation value is observed for six-mode case. The proposed method offers alternative way to improve the correlation without using elaborated ANN. |
| Rights: | ©2021. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/ | | http://creativecommons.org/licenses/by-nc-nd/4.0/ |
| Type: | article (author version) |
| URI: | http://hdl.handle.net/2115/90541 |
| Appears in Collections: | 情報科学院・情報科学研究院 (Graduate School of Information Science and Technology / Faculty of Information Science and Technology) > 雑誌発表論文等 (Peer-reviewed Journal Articles, etc)
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Submitter: 藤澤 剛
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