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We study the problem of estimating an unknown deterministic signal that is observed through an unknown deterministic observation matrix and additive noise under the regularized residual error criterion. In this framework, we introduce a robust approach to this problem and consider the performance of an estimator relative to the performance of the least squares (LS) estimator tuned to the underlying...
In this paper, we consider the linear estimation problem under structured data uncertainties. A robust algorithm is presented under bounded uncertainties under the mean square error (MSE) criterion. The performance of the linear estimator is defined relative to the performance of the linear minimum MSE (MMSE) estimator tuned to the underlying unknown data uncertainties, i.e., the introduced algorithm...
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