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TSP
2008

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Linear Regression With Gaussian Model Uncertainty: Algorithms and Bounds

13 years 10 months ago

Linear Regression With Gaussian Model Uncertainty: Algorithms and Bounds

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In this paper, we consider the problem of estimating an unknown deterministic parameter vector in a linear regression model with random Gaussian uncertainty in the mixing matrix. We prove that the maximum-likelihood (ML) estimator is a (de)regularized least squares estimator and develop three alternative approaches for finding the regularization parameter that maximizes the likelihood. We analyze the performance using the Cram

Ami Wiesel, Yonina C. Eldar, Arie Yeredor

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Added	16 Dec 2010
Updated	16 Dec 2010
Type	Journal
Year	2008
Where	TSP
Authors	Ami Wiesel, Yonina C. Eldar, Arie Yeredor

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