Abstract

Two semiparametric algorithms to recover a nonlinear characteristic in a Hammerstein system are proposed. Both are obtained by incorporating a parametric component into the kernel nonparametric algorithm. For small number of observations, their identification errors are smaller than that of the purely nonparametric algorithm. The same idea is also proposed for identification of linear dynamic component. Parametric instrumental variables estimate is elastically substituted by the nonparametric correlation-based method, when the number of observations tends to infinity.

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