Block-oriented nonlinear models are popular in nonlinear system identification because of
their advantages of being simple to understand and easy to use. Many different identification …

Abstract Using Artificial Neural Networks (ANN) for nonlinear system identification has
proven to be a promising approach, but despite of all recent research efforts, many practical …

Nonlinear state-space identification for dynamical systems is most often performed by
minimizing the simulation error to reduce the effect of model errors. This optimization …

This paper presents a record of the participation of the authors in a workshop on nonlinear
system identification held in 2016. It provides a summary of a keynote lecture by one of the …

This paper addresses the problem of Wiener–Hammerstein (LNL) system identification. We
present two estimates, which recover the static nonlinear characteristic and the linear …

Wiener–Hammerstein models are flexible, well known and often studied. The main
challenge in identifying a Wiener–Hammerstein model is to distinguish the linear time …

The Wiener-Hammerstein (WH) system is a popular and easy to understand class of Volterra
nonlinear dynamical system. It consists of a static nonlinearity positioned between two …

Block-oriented nonlinear models are popular in nonlinear modeling because of their
advantages to be quite simple to understand and easy to use. To increase the flexibility of …

This paper develops and analyses a novel method for identifying Wiener–Hammerstein
models, ie models consisting of two linear dynamic parts with a static non-linearity in …

The Wiener-Hammerstein (WH) system is the most popular type of the Volterra nonlinear
dynamical system. It is a combination of two dynamical subsystems, separated by a static …