A Shrinkage Linear Minimum Mean Square Error Estimator

作者：Wen, Chao Kai^*; Chen, Jung Chieh; Ting, Pangan

来源：IEEE Signal Processing Letters, 2013, 20(12): 1179-1182.

DOI：10.1109/LSP.2013.2283725

• Estimator
• high-dimensional data
• LMMSE
• sample covariance
• shrinkage

The conventional linear minimum mean square error (LMMSE) estimator is commonly implemented through the sample covariance matrix. This estimator can only be implemented if the sample size is higher than the observation dimension. Moreover, this estimator performs poorly when the sample size is not sufficiently large. To address this problem, we propose a new shrinkage LMMSE estimator. The proposed estimator performs efficiently over a wide range of observation dimensions and sample sizes. In contrast to existing methods, the proposed estimator can be applied if M >= N. Even if M < N, the proposed estimator performs more efficiently than existing estimators.

• 出版日期2013-12
• 单位中山大学