Abstract
Features of the linear optimal estimator (LOE) that minimizes the root mean-square (RMS) criterion in the class of linear estimates in nonlinear problems are investigated. The equivalent linear models for measurements have been introduced for the LOE and the Cramer-Rao Bound. The features of the LOE in comparison with the optimal Bayesian estimator, which corresponds to the conditional mean, are studied. Some examples are considered to illustrate the results obtained.
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