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- W2781326273 abstract "This paper addresses the problem of maximum likelihood parameter estimation in linear models a!ected by Gaussian noise, whose mean and covariance matrix are uncertain. The proposed estimate maximizes a lower bound on the worst-case (with respect to the uncertainty) likelihood of the measured sample, and is computed solving a semidenite optimization problem (SDP). The problem of linear robust estimation is also studied in the paper, and the statistical and optimality properties of the resulting linear estimator are discussed. ( 2001 Elsevier Science Ltd. All rights reserved." @default.
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- W2781326273 date "2001-01-01" @default.
- W2781326273 modified "2023-09-24" @default.
- W2781326273 title "Brief Paper Robust maximum likelihood estimation in the linear model q" @default.
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