Abstract
This paper is concerned with the identification of a discrete-time Wiener model, composed of a linear time-invariant (LTI) system followed by a static monotonous nonlinearity. Introducing a set of basis functions for the inverse nonlinearity, we define a criterion for the Wiener model identification according to the generalized error structure. We then develop a method of alternately identifying system matrices of the LTI system by a subspace method and the inverse nonlinearity by the least-squares method. Some numerical results are included.
