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Titlebook: Schwarz Methods and Multilevel Preconditioners for Boundary Element Methods; Ernst P. Stephan,Thanh Tran Book 2021 The Editor(s) (if appli

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發(fā)表于 2025-3-21 16:09:12 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書目名稱Schwarz Methods and Multilevel Preconditioners for Boundary Element Methods
編輯Ernst P. Stephan,Thanh Tran
視頻videohttp://file.papertrans.cn/863/862206/862206.mp4
概述Unique book so far devoted to preconditioners for boundary element discritizations of first-kind integral equations.Thorough explanations of the mechanism of preconditioners and necessary tools for an
圖書封面Titlebook: Schwarz Methods and Multilevel Preconditioners for Boundary Element Methods;  Ernst P. Stephan,Thanh Tran Book 2021 The Editor(s) (if appli
描述.This book provides a comprehensive examination of preconditioners for boundary element discretisations of first-kind integral equations. Focusing on domain-decomposition-type and multilevel methods, it allows readers to gain a good understanding of the mechanisms and necessary techniques in the analysis of the preconditioners. These techniques are unique for the discretisation of first-kind integral equations since the resulting systems of linear equations are not only large and ill-conditioned, but also dense.. .The book showcases state-of-the-art preconditioning techniques for boundary integral equations, presenting up-to-date research. It also includes a detailed discussion of Sobolev spaces of fractional orders to familiarise?readers with important mathematical tools for the analysis. Furthermore, the concise overview of adaptive BEM, hp-version BEM, and coupling of FEM-BEM provides efficient computational tools for solving practical problems with applications in science and?engineering..
出版日期Book 2021
關(guān)鍵詞domain decomposition; multilevel; preconditioner; boundary element; boundary integral equation; FEM-BEM c
版次1
doihttps://doi.org/10.1007/978-3-030-79283-1
isbn_softcover978-3-030-79285-5
isbn_ebook978-3-030-79283-1
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
The information of publication is updating

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of IR models, which by 2000 consisted of relatively isolated views on TF-IDF (Term-Frequency times Inverse-Document-Frequency) as the weighting scheme in the vector-space model (VSM), the probabilistic relevance framework (PRF), the binary independence retrieval (BIR) model, BM25 (Best-Match Version
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Ernst P. Stephan,Thanh Tranls, which by 2000 consisted of relatively isolated views on TF-IDF (Term-Frequency times Inverse-Document-Frequency) as the weighting scheme in the vector-space model (VSM), the probabilistic relevance framework (PRF), the binary independence retrieval (BIR) model, BM25 (Best-Match Version 25, the m
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Ernst P. Stephan,Thanh Tranroadband technologies. Unfortunately, speech documents are inherently hard to browse because of their transient nature. One approach to this problem is to label segments of a spoken document with keyphrases that summarise them. In this paper, we investigate an approach for automatically extracting k
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Ernst P. Stephan,Thanh Tranoven to be effective for the task, which are often trained with click-through data. One technical challenge with the approach is that it is hard to train a model for tail queries and tail documents for which there are not enough clicks. In this paper, we propose to address the challenge by learning
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