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On the Gaussian Cramér-Rao Bound for Blind Single-Input Multiple-Output System Identification: Fast and Asymptotic Computations
The Cramér-Rao Bound (CRB) is a powerful tool to assess the performance limits of a parameter estimation problem for a given statistical model. In particular, the Gaussian CRB (i.e., the CRB obtained assuming the data are Gaussian) corresponds to the worst case; giving the largest CRB among a large class of data distributions. This makes it very useful in practice since optimizing under the Gaussian data assumption can be interpreted as a min-max optimization (i.e., minimizing the largest CRB).doi:10.1109/access.2020.3022710 fatcat:snvhiyjsdjdtteal3f5a2ka6yu