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このアイテムの引用には次の識別子を使用してください:
http://hdl.handle.net/10119/9098
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| タイトル: | Notes on “reducing algorithm complexity for computing an aggregate uncertainty measure” |
| 著者: | Huynh, Van-Nam
Nakamori, Yoshiteru |
| キーワード: | Aggregate uncertainty (AU)
Computational complexity
Dempster-Shafer theory
Uncertainty measures |
| 発行日: | 2010-01 |
| 出版者: | Institute of Electrical and Electronics Engineers (IEEE) |
| 誌名: | IEEE Transactions on Systems, Man and Cybernetics - Part A: Systems and Humans |
| 巻: | 40 |
| 号: | 1 |
| 開始ページ: | 205 |
| 終了ページ: | 209 |
| DOI: | 10.1109/TSMCA.2009.2030962 |
| 抄録: | In a recent paper, Liu et al. (2007) have proposed the so-called F-algorithm which conditionally reduces the computational complexity of the Meyerowitz-Richman-Walker algorithm for the computation of the aggregate uncertainty (AU) measure in Dempster-Shafer theory of evidence, along with an illustration of its application in a practical scenario of target identification. In this short article, we will point out several technical mistakes, which some of them lead to some inexact or incomplete statements in Liu et al.'s paper. The corrections of these mistakes will be made, as well as some further improvement and results will be derived. |
| Rights: | Copyright (C) 2010 IEEE. Reprinted from IEEE Transactions on Systems, Man and Cybernetics - Part A: Systems and Humans, 40(1), 2010, 205-209. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of JAIST's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to pubs-permissions@ieee.org. By choosing to view this document, you agree to all provisions of the copyright laws protecting it. |
| URI: | http://hdl.handle.net/10119/9098 |
| 資料タイプ: | publisher |
| 出現コレクション: | a10-1. 雑誌掲載論文 (Journal Articles)
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