Technical Report 2021-006

When are Errors-in-Variables Aspects Particularly Important to Consider in System Identification?

Torsten Söderström and Umberto Soverini

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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