In a world of almost permanent and rapidly increasing electronic data availability,
techniques of filtering, compressing, and interpreting this data to transform it into valuable …

Addresses parametric system identification of linear and nonlinear dynamic systems by
analysis of the input and output signals. Specifically, the authors investigate the relationship …

Recently published data from Reeves et al.(2011) on the fluxes of 1.8–3.5 MeV electrons at
geostationary orbit are subjected to Error Reduction Ratio (ERR) analysis in order to identify …

The last fifteen years have witnessed a tremendous resurgence in research and applications
in the area of higher-order statistics (HOS), a broad term encompassing statistical …

This paper is a summary of the research development in the rational (total) nonlinear
dynamic modelling over the last two decades. Total nonlinear dynamic systems are defined …

A new hybrid model structure combing polynomial models with multiresolution wavelet
decompositions is introduced for nonlinear system identification. Polynomial models play an …

Identification of linear and nonlinear time-varying systems is investigated and a new wavelet
model identification algorithm is introduced. By expanding each time-varying coefficient …

In this study an error back propagation (BP) parameter estimation algorithm is derived for a
class of non-linear dynamic rational models. By combining an orthogonal correlation test …

The identification of nonlinear time-varying systems using linear-in-the-parameter models is
investigated. An efficient common model structure selection (CMSS) algorithm is proposed …

Modelling and identification is one of the major areas of control engineering and the theory
and practice of linear system identification is now well established [1][2]. During the past …