This paper focuses on a novel bias-free least squares (BFLS) parameter estimation approach which has recently received attention in the system identi cation and control literature. First the BFLS parameter estimator is derived in a more general setting than in the original works. Then the paper goes to show that any BFLS parameter estimator can be exactly realized in the well-studied class of weighted instrumental-variable (WIV) estimators. The paper also includes a comparative performance study of the unweighted estimators in the BFLS and IV classes.
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