Robust parametric approach for impulse response estimation

The authors consider impulse response estimation of linear time-invariant causal systems based on input-output measurements. In particular, their interest is in developing estimates that are robust against outliers and distributional uncertainties. They present a method which uses Huber's functions as the criterion for fitting a parametric model to the input-output observations. The estimates from this method are compared with the estimates from a similar parametric approach but which uses the conventional quadratic criterion, and also with the estimates from some nonparametric approaches. Results from simulation clearly show that the estimates from the parametric approach using Huber's function are most robust of all the estimates considered.<>