論文

査読有り
2008年5月

Approximating the best linear unbiased estimator of non-Gaussian signals with Gaussian noise

IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS
  • Masashi Sugiyama
  • ,
  • Motoaki Kawanabe
  • ,
  • Gilles Blanchard
  • ,
  • Klaus-Robert Mueller

E91D
5
開始ページ
1577
終了ページ
1580
記述言語
英語
掲載種別
研究論文(学術雑誌)
DOI
10.1093/ietisy/e91-d.5.1577
出版者・発行元
IEICE-INST ELECTRONICS INFORMATION COMMUNICATIONS ENG

Obtaining the best linear unbiased estimator (BLUE) of noisy signals is a traditional but powerful approach to noise reduction. Explicitly computing the BLUE usually requires the prior knowledge of the noise covariance matrix and the subspace to which the true signal belongs. However, such prior knowledge is often unavailable in reality, which prevents us from applying the BLUE to real-world problems. To cope with this problem, we give a practical procedure for approximating the BLUE without such prior knowledge. Our additional assumption is that the true signal follows a non-Gaussian distribution while the noise is Gaussian.

Web of Science ® 被引用回数 : 1

リンク情報
DOI
https://doi.org/10.1093/ietisy/e91-d.5.1577
Web of Science
https://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=JSTA_CEL&SrcApp=J_Gate_JST&DestLinkType=FullRecord&KeyUT=WOS:000256860900041&DestApp=WOS_CPL
URL
http://dblp.uni-trier.de/db/journals/ieicet/ieicet91d.html#journals/ieicet/SugiyamaKBM08
ID情報
  • DOI : 10.1093/ietisy/e91-d.5.1577
  • ISSN : 1745-1361
  • DBLP ID : journals/ieicet/SugiyamaKBM08
  • Web of Science ID : WOS:000256860900041

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