neural networks are applicable in identification systems from input-output data. in this report, we analyze thehammerstein-wiener models and identify them. thehammerstein-wiener systems are the simplest type of block orientednonlinear systems where the linear dynamic block issandwiched in between two static nonlinear blocks, whichappear in many engineering applications; the aim of nonlinearsyst...

The nonlinear system becomes an area with numerous investigations over the past decades. The conventional modal analysis could not be  applied on nonlinear continuous system which makes it impossible to construct the reduced order models and obtain system response based on limited number of measurement points. Nonlinear normal modes provide a useful tool for extending modal analysis to nonlinea...

A high-dimensional regression space usually causes problems in nonlinear system identification. However, if the regression data are contained in (or spread tightly around) some manifold, the dimensionality can be reduced. This paper presents a use of dimension reduction techniques to compose a two-step identification scheme suitable for high-dimensional identification problems with manifold-val...

The present bibliography represents a comprehensive list of references on nonlinear system identification and its applications in signal processing, communications, and biomedical engineering. An attempt has been made to make this bibliography complete by listing most of the existing references up to the year 2000 and by providing a detailed classification group.

Nonlinear function approximation is one of the most important tasks in system analysis and identification. Several models have been presented to achieve an accurate approximation on nonlinear mathematics functions. However, the majority of the models are specific to certain problems and systems. In this paper, an evolutionary-based wavelet neural network model is proposed for structure definiti...

This paper deals with multiobjective nonlinear system identification applied when modelling the relation of firing angle and equivalent reactance of a thyristor controlled series capacitor (TCSC). The mathematical representation chosen is NARMAX (Nonlinear AutoRegressive Moving Average with eXogenous inputs) due to its capability in modelling nonlinear systems and in using prior information. Th...

Because of the existing interactions among the variables of a multiple input-multiple output (MIMO) nonlinear system, its identification is a difficult task, particularly in the presence of uncertainties. Cement rotary kiln (CRK) is a MIMO nonlinear system in the cement factory with a complicated mechanism and uncertain disturbances. The identification of CRK is very important for different pur...