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Abstract
The statistical regularizators for optimal linear estimutors for unknown parameters in general linear model with arbitary nonnegative covariance structure are obtained on basis of theory of regularizing operators. Conditions guaranteeing closencss of rcgularized estimator to optimal estimator are easily satisfied by appropriate choice of regularization parameter in accordance with the given level of uncertainty. Application of regularization approach to design of stable filters is presented. Numerical example is given to illustrate an efficiency of proposed approach.
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