September 2021
Abstract:When recorded signals are corrupted by noise on both input and output sides, all standard identification methods give biased parameter estimates, due to the presence of input noise. This report discusses in what situations such a bias is large and, consequently, when the errors-in-variables identification methods are to be preferred.
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