Estimating complex covariance matrices
Estimating complex covariance matrices
复制标题
估计复杂的协方差矩阵
DOI：
10.1109/acssc.2004.1399547
复制
发表时间：
2004
期刊：
影响因子：
--
通讯作者：
M. Lundbergt
中科院分区：
文献类型：
--
作者：
L. Svensson;M. Lundbergt
考虑了复协方差矩阵的估计问题。我们的目标是获得一个良好的行为估计，规避标准样本协方差和正则化估计的弱点。为此，我们使用变分技术，以前已成功地应用于真实的数据的情况下。作为一个侧面的结果，一个重要的身份复杂的Wishart分布也来自。仿真结果表明，与样本协方差和正则化估计相比，有了很大的改进。
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.