Abstract. The aim of the given paper is the development of an approach for parametric identification of Hammerstein systems with piecewise linear nonlinearities, i.e., when the sat...
In nonlinear system identification, the system is often represented as a series of blocks linked together. Such block-oriented models are built with static nonlinear subsystems an...
Both direct and indirect methods exist for identifying continuous-time linear systems. A direct method estimates continuous-time input and output signals from their samples and the...
We present a two-step method for identifying SISO Hammerstein systems. First, using a persistent input with retrospective cost optimization, we estimate a parametric model of the l...
Anthony M. D'Amato, Kenny S. Mitchell, Bruno Ot&aa...
This paper adresses the variance quantification problem for system identification based on the prediction error framework. The role of input and model class selection for the auto-...