This paper aims at developing a Recursive Parametric Estimation (RPE) algorithm for Multi-
Input Single-Output (MISO) and Multi-Input Multi-Output (MIMO) nonlinear systems …

In the present study, strength of meta-heuristic computing techniques is exploited for
estimation problem of Hammerstein controlled auto regressive auto regressive moving …

This paper investigates the parameter estimation of Hammerstein–Wiener systems whose
linear subsystems are observable state-space models. The particle swarm optimization …

In this paper, we develop a novel filtering algorithm for Hammerstein-Wiener State-Space
Systems. The likelihood function of the noisy nonlinear output signal given the system state …

Hammerstein-Wiener models have been proved to be suitable in modelling a class of typical
non-linear dynamic systems. This paper aims at developing a Hammerstein-Wiener Neural …

This paper proposes two iterative procedures based on over-parameterisation and
optimisation approaches for the identification of nonlinear systems which can be described …

In this paper, we develop a novel Bayesian smoothing method for obtaining the smoothed
probability density functions of Hammerstein-Wiener state-space systems and the …

This paper presents black-box modeling of power systems using both linear and nonlinear
methods. These methods contain wavelet-based and Hammerstein-Wiener as nonlinear …

A novel data‐driven learning approach of nonlinear system represented by neural fuzzy
Hammerstein‐Wiener model is presented. The Hammerstein‐Wiener system has two static …

In this paper unscented Kalman filter parameter estimation algorithm is stated for
identification of dynamic systems' model which may be considered as the Hammerstein …