Estimating complex covariance matrices
Paper in proceedings, 2004

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.

Author

Lennart Svensson

Chalmers, Signals and Systems, Signalbehandling och medicinsk teknik, Signal Processing

Magnus Lundberg

Chalmers, Signals and Systems, Signalbehandling och medicinsk teknik, Signal Processing

Proc. 38th Asilomar conference on signals, systems and computers

Subject Categories

Probability Theory and Statistics

Signal Processing

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Created

10/8/2017