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Estimating complex covariance matrices
Chalmers University of Technology.
2004 (English)In: Conference Record of the Thirty-Eighth Asilomar Conference on Signals, Systems and Computers, IEEE Communications Society, 2004, Vol. 2, 2151-2154 p.Conference paper (Refereed)
Abstract [en]

The problem of estimating complex covariance matrices is considered. The objective is to obtain a well behaving estimator that circumvents the weaknesses of the standard sample covariance and regularized estimators. To this end, we use a variational technique that previously has been successfully applied in the real data case. As a side result, an important identity for complex Wishart distributions is also derived. Simulations indicate substantial improvements compared to both the sample covariance and the regularized estimator.

Place, publisher, year, edition, pages
IEEE Communications Society, 2004. Vol. 2, 2151-2154 p.
Research subject
Signal Processing
URN: urn:nbn:se:ltu:diva-34473DOI: 10.1109/ACSSC.2004.1399547ScopusID: 21644444542Local ID: 8afb4e90-f25d-11df-8b36-000ea68e967bISBN: 0-7803-8622-1 (print)OAI: diva2:1007724
Asilomar Conference on Signals, Systems and Computers : 07/11/2004 - 10/11/2004
Upprättat; 2004; 20101117 (ysko)Available from: 2016-09-30 Created: 2016-09-30

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Lundberg, Magnus

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