Parametric Identification of Hammerstein Systems With Consistency Results Using Stochastic Inputs

The extended least squares algorithm is applied to identify the Hammerstein system, where the nonlinear static function
f
(·) is expressed as a linear combination of basic functions with unknown coefficients. Strong consistency of the estimates is established and their convergent rates are obtained as well.