This paper examines the use of a so-called “generalised Hammerstein–Wiener” model structure that is formed as the concatenation of an arbitrary number of Hammerstein systems. The latter are taken here to be memoryless nonlinearities followed by linear time invariant dynamics. Hammerstein, Wiener, Hammerstein–Wiener and Wiener–Hammerstein models are all special cases of this structure. The param...

This paper examines the use of a so-called “generalised Hammerstein–Wiener” model structure that is formed as the concatenation of an arbitrary number of Hammerstein systems. The latter are taken here to be memoryless non-linearities followed by linear time invariant dynamics. Hammerstein, Wiener, Hammerstein–Wiener and Wiener–Hammerstein models are all special cases of this structure. The para...

Introduction: Block-oriented structures are useful to model a nonlinear system. Applications range from RF amplifiers over chemical processes to physiological systems [1]. A block-oriented model consists of two types of blocks: Linear Time Invariant (LTI) and static nonlinear blocks. The most simple block-oriented model structures are the Wiener (a LTI block followed by a static nonlinear block...

The identification algorithm of Wiener-Hammerstein nonlinear model is proposed in the paper. When the nonlinearity in the Wiener-Hammerstein model is approximated by polynomial or spline function, the identification algorithms can be implemented iteratively, and the compensator for the nonlinear distortion is given by using the estimated Wiener-Hammerstein model and its inverse. A numerical sim...

In this paper, block-oriented systems with linear parts based on Laguerre functions is used to approximation of a cone crusher dynamics. Adaptive recursive least squares algorithm is used to identification of Laguerre model. Various structures of Hammerstein, Wiener, Hammerstein-Wiener models are tested and the MATLAB simulation results are compared. The mean square error is used for models val...

System identification is very important to technical and nontechnical areas. All physical systems are nonlinear to some extent and it is natural better to use nonlinear model to describe a real system. The Wiener and Hammerstein systems are proved to be good descriptions of nonlinear dynamic systems in which the nonlinear static subsystems and linear dynamic subsystems are separated in differen...

a new approach is introduced to estimate the formal information of neurons. formal information, mainly discusses about the aspects of the response that is related to the stimulus. estimation is based on introducing a mathematical nonlinear model with hammerstein-wiener system estimator. this method of system identification consists of three blocks to completely describe the nonlinearity of inpu...

This paper develops and illustrates a new maximum-likelihood based method for the identification of Hammerstein–Wiener model structures. A central aspect is that a very general situation is considered wherein multivariable data, non-invertible Hammerstein and Wiener nonlinearities, and coloured stochastic disturbances both before and after the Wiener nonlinearity are all catered for. The method...

While there exists a substantial literature on the identification of Hammerstein and Wiener models, the identification of WienerHammerstein models has received considerably less attention yet this is a model class of very great practical importance. This paper proposes an elegant approach to estimating Wiener-Hammerstein systems from measured data.

The class of nonlinear dynamic systems which can be represented by the block-oriented models, ie, by interconnection of linear dynamic and nonlinear static subsystems, has been studied by many authors. In the simplest case the models consist of a combination of two blocks giving the so-called Hammerstein (nonlinear-linear) and Wiener (linear-nonlinear) models and there are many methods for nonl...