2006年
Obtaining the best linear unbiased estimator of noisy signals by non-Gaussian component analysis
2006 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING, VOLS 1-13
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- 開始ページ
- 3059
- 終了ページ
- 3062
- 記述言語
- 英語
- 掲載種別
- 研究論文(国際会議プロシーディングス)
- DOI
- 10.1109/ICASSP.2006.1660727
- 出版者・発行元
- IEEE
Obtaining the best linear unbiased estimator (BLUE) of noisy signals is a traditional but powerful approach to noise reduction. Explicitly computing BLUE usually requires the prior knowledge of the subspace to which the true signal belongs and the noise covariance matrix. However, such prior knowledge is often unavailable in reality, which prevents us from applying BLUE to real-world problems. In this paper, we therefore give a method for obtaining BLUE without such prior knowledge. Our additional assumption is that the true signal follows a non-Gaussian distribution while the noise is Gaussian.
- リンク情報
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- DOI
- https://doi.org/10.1109/ICASSP.2006.1660727
- DBLP
- https://dblp.uni-trier.de/rec/conf/icassp/SugiyamaKBSM06
- Web of Science
- https://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=JSTA_CEL&SrcApp=J_Gate_JST&DestLinkType=FullRecord&KeyUT=WOS:000245559903176&DestApp=WOS_CPL
- URL
- http://dblp.uni-trier.de/db/conf/icassp/icassp2006-3.html#conf/icassp/SugiyamaKBSM06
- ID情報
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- DOI : 10.1109/ICASSP.2006.1660727
- ISSN : 1520-6149
- DBLP ID : conf/icassp/SugiyamaKBSM06
- Web of Science ID : WOS:000245559903176