This article reviews and investigates several basic recursive parameter identification
methods for a general stochastic system with colored noise (ie, output-error autoregressive …

COVID-19 has disrupted normal life and has enforced a substantial change in the policies,
priorities and activities of individuals, organisations and governments. These changes are …

Least squares is an important method for solving linear fitting problems and quadratic
optimization problems. This paper explores the properties of the least squares methods and …

For equation‐error autoregressive moving average systems, that is, Box–Jenkins systems,
this paper presents a filtered auxiliary model generalized extended stochastic gradient …

Nonlinear system identification is an extremely broad topic, since every system that is not
linear is nonlinear. That makes it impossible to give a full overview of all aspects of the fi eld …

By using the collected batch data and the iterative search, and based on the filtering
identification idea, this article investigates and proposes a filtered multi‐innovation …

In this paper, we introduce Symplectic ODE-Net (SymODEN), a deep learning framework
which can infer the dynamics of a physical system, given by an ordinary differential equation …

Integrity is one criteria to evaluate GNSS performance, which was first introduced in the
aviation field. It is a measure of trust which can be placed in the correctness of the …

Control in the presence of uncertainty is one of the main topics of modern control theory. In
the formulation of any control problem there is always a discrepancy between the actual …

Most of the currently used techniques for linear system identification are based on classical
estimation paradigms coming from mathematical statistics. In particular, maximum likelihood …