Polyspectral and cyclostationary approaches for identification of closed-loop systems

Conventional spectral analysis fails in identifying systems operating with feedback from noisy input-output data. It is shown that polyspectral and cyclic methods can identify closed-loop systems with data corrupted by a class of stationary and cyclostationary noise. The class is specified and nonparametric transfer function estimators are developed and simulated.<
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