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Minimum variance beamformers are widely used for array signal processing. It is known that the diagonal loading method can improve the robustness against mismatches caused by the imprecise steering vector (or the channel vector) and the noise covariance matrix. Instead of concentrating on one aspect of the mismatches and assuming perfect knowledge of the other, we handle both estimation error in the...
We study the problem of linear filter optimization with finite sample size, which has wide applications such as beamformer design in wireless communications and portfolio optimization in finance. Traditional methods in both fields are not robust against the imprecise channel vector and the noise covariance matrix (or the mean return and the covariance of assets in finance) due to finite sample size...
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