Volterra-series-based nonlinear system modeling and its engineering applications: A state-of-the-art review
CM Cheng, ZK Peng, WM Zhang, G Meng - Mechanical Systems and Signal …, 2017 - Elsevier
Nonlinear problems have drawn great interest and extensive attention from engineers,
physicists and mathematicians and many other scientists because most real systems are …
physicists and mathematicians and many other scientists because most real systems are …
A bibliography on nonlinear system identification
GB Giannakis, E Serpedin - Signal Processing, 2001 - Elsevier
The present bibliography represents a comprehensive list of references on nonlinear system
identification and its applications in signal processing, communications, and biomedical …
identification and its applications in signal processing, communications, and biomedical …
Identification of certain time-varying nonlinear Wiener and Hammerstein systems
AE Nordsjo, LH Zetterberg - IEEE transactions on signal …, 2001 - ieeexplore.ieee.org
The problem of identification and tracking of time-varying nonlinear systems is addressed. In
particular, the Wiener system that consists of a dynamic time-varying linear part followed by …
particular, the Wiener system that consists of a dynamic time-varying linear part followed by …
System identification using Hammerstein model optimized with differential evolution algorithm
This paper aims to improve Hammerstein model for system identification area. Hammerstein
model block structure is formed by cascade of linear and nonlinear parts. In literature …
model block structure is formed by cascade of linear and nonlinear parts. In literature …
Identification of a class of nonlinear systems under stationary non-Gaussian excitation
JC Ralston, AM Zoubir… - IEEE Transactions on …, 1997 - ieeexplore.ieee.org
This paper provides new solutions to the nonlinear system identification problem when the
input to the system is a stationary non-Gaussian process. We propose the use of a model …
input to the system is a stationary non-Gaussian process. We propose the use of a model …
Identification of time-varying Hammerstein systems from ensemble data
M Lortie, RE Kearney - Annals of Biomedical Engineering, 2001 - Springer
In this paper, we describe a new technique to identify rapidly time-varying Hammerstein
systems from ensembles of input–output realizations. The technique involves two steps. A …
systems from ensembles of input–output realizations. The technique involves two steps. A …
System modeling using basis functions and application to echo cancellation.
LSH Ngia - 2002 - elibrary.ru
In the first part of the thesis, the investigated model (or filter) structures and parameter
estimation algorithms are described. The focus is on the parameter estimation algorithms, for …
estimation algorithms are described. The focus is on the parameter estimation algorithms, for …
Improvements of nonlinear dynamic modeling of hot-film MAF sensor
KJ Xu, J Zhang, XF Wang, Q Teng, J Tan… - Sensors and Actuators A …, 2008 - Elsevier
The operating procedure of engine requires that the mass air flow (MAF) sensor can
measure the pulsation air flow accurately. Therefore the MAF sensor must possess fast …
measure the pulsation air flow accurately. Therefore the MAF sensor must possess fast …
Separable nonlinear least-squares methods for on-line estimation of neural nets Hammerstein models
LSH Ngia - Neural Networks for Signal Processing X …, 2000 - ieeexplore.ieee.org
When the estimation of Hammerstein models is based on a minimization of least-squares
error criterion, the minimization problem becomes separable with respect to the linear …
error criterion, the minimization problem becomes separable with respect to the linear …