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Scalable Estimation on Linear and Nonlinear Regression Models via Decentralized Processing: Adaptive LMS Filter and Gaussian Process Regression / 分散処理による線形・非線形回帰モデルでのスケーラブルな推定:適応LMSフィルタとガウス過程回帰

京都大学 / 新制・課程博士 / 博士(情報学) / 甲第23588号 / 情博第782号 / 新制||情||133(附属図書館) / 京都大学大学院情報学研究科システム科学専攻 / (主査)教授 田中 利幸, 教授 下平 英寿, 准教授 櫻間 一徳 / 学位規則第4条第1項該当 / Doctor of Informatics / Kyoto University / DGAM

Identiferoai:union.ndltd.org:kyoto-u.ac.jp/oai:repository.kulib.kyoto-u.ac.jp:2433/266686
Date24 November 2021
CreatorsNakai, Ayano
Contributors中井, 彩乃, ナカイ, アヤノ
PublisherKyoto University, 京都大学
Source SetsKyoto University
LanguageEnglish
Detected LanguageEnglish
Typedoctoral thesis, Thesis or Dissertation
Rights学位規則第9条第2項により要約公開, In reference to IEEE copyrighted material which is used with permission in this thesis, the IEEE does not endorse any of Kyoto University’s products or services. Internal or personal use of this material is permitted. If interested in reprinting/republishing IEEE copyrighted material for advertising or promotional purposes or for creating new collective works for resale or redistribution, please go to http://www.ieee.org/publications_standards/publications/rights/rights_link.html to learn how to obtain a License from RightsLink. If applicable, University Microfilms and/or ProQuest Library, or the Archives of Canada may supply single copies of the dissertation.; Part I in this dissertation is based on ""An acceleration method of sparse diffusion LMS based on message propagation"" [1], by the same author, which appeared in IEICE Transactions on Communications, Copyright ©2021 IEICE. The material in this dissertation was presented in part at IEICE Transactions on Communications [1], and a part of the figures of this dissertation is reused from [1] under the permission of the IEICE.; Part Ⅱ: Reproduced with permission from Springer Nature.

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