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  Reconstructing signals from noisy data with unknown signal and noise covariance

Oppermann, N., Robbers, G., & Enßlin, T. A. (2013). Reconstructing signals from noisy data with unknown signal and noise covariance. In U. VonToussaint (Ed.), Bayesian Inference and Maximum Entropy Methods in Science and Engineering (pp. 122-129). doi:10.1063/1.4819991.

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Item Permalink: http://hdl.handle.net/11858/00-001M-0000-0014-B067-2 Version Permalink: http://hdl.handle.net/11858/00-001M-0000-002A-3AB5-5
Genre: Conference Paper

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 Creators:
Oppermann, N.1, Author              
Robbers, G.1, Author              
Enßlin, T. A.1, Author              
Affiliations:
1Computational Structure Formation, MPI for Astrophysics, Max Planck Society, ou_2205642              

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Language(s): eng - English
 Dates: 2013
 Publication Status: Published online
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Method: -
 Identifiers: DOI: 10.1063/1.4819991
Other: LOCALID: 1857329
 Degree: -

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Title: 32nd International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering (MAXENT)
Place of Event: Garching, Germany
Start-/End Date: 2012-07-15 - 2012-07-20

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Title: Bayesian Inference and Maximum Entropy Methods in Science and Engineering
Source Genre: Proceedings
 Creator(s):
VonToussaint, U., Editor
Affiliations:
-
Publ. Info: -
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 122 - 129 Identifier: ISBN: 978-0-7354-1179-1

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Title: AIP Conference Proceedings
Source Genre: Series
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Publ. Info: Melville, NY, USA : American Institute of Physics
Pages: - Volume / Issue: 1553 Sequence Number: - Start / End Page: - Identifier: ISSN: 0094-243X