A huge class of nonlinear dynamic systems can be approximated by the Nonlinear
AutoRegressive with eXogenous inputs (NARX) models. This paper proposes a novel …

A forward and backward least angle regression (LAR) algorithm is proposed to construct the
nonlinear autoregressive model with exogenous inputs (NARX) that is widely used to …

Abstract Nonlinear Auto-Regressive model with eXogenous input (NARX) is one of the most
popular black-box model classes that can describe many nonlinear systems. The structure …

Identification of nonlinear dynamic systems remains challenging nowadays. Although the
nonlinear autoregressive with exogenous input (NARX) model is flexible to describe …

In past years, the system identification area has emphasized the identification of nonlinear
dynamic systems. In this field, polynomial nonlinear autoregressive with exogenous (NARX) …

A hybrid dynamics modeling method based on expectation‐maximization (EM) is proposed
in this article. The dynamics include continuous dynamic equations that depend on the …

As an emerging non-parametric modeling technique, the methodology of support vector
regression blazed a new trail in identifying complex nonlinear systems with superior …

As an innovative sparse kernel modeling method, support vector regression (SVR) has been
regarded as the state-of-the-art technique for regression and approximation. In the support …

An orthogonal least squares technique for basis hunting (OLS-BH) is proposed to construct
sparse radial basis function (RBF) models for NARX-type nonlinear systems. Unlike most of …

In this paper, we design a transfer sparse identification algorithm under the Bayesian
framework through introducing other system knowledge into the system to be identified. This …