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 …

This paper studies the parameter identification problem for a large-scale multivariable
systems. In terms of the identification obstacle causing by huge amounts of parameters of …

The parameter estimation methods for the nonlinear exponential autoregressive model are
investigated in this paper. We develop a forgetting factor gradient parameter estimation …

This paper considers the parameter identification problems of a Volterra nonlinear system. In
order to overcome the excessive calculation amount of the Volterra systems, a hierarchical …

The current mobility situation is constantly changing as people are increasingly moving to
urban areas. Therefore, a flexible mode of transport with high-capacity passenger trains and …

This paper mainly investigates the issue of parameter identification for the fractional‐order
input nonlinear output error autoregressive (IN‐OEAR) model. In order to avoid the problem …

This article investigates the parameter identification problems of the stochastic systems
described by the input‐nonlinear output‐error (IN‐OE) model. This IN‐OE model consists of …

To further improve the line transport capacity, virtual coupling has become a frontier hot topic
in the field of rail transit. Specially, the safe and efficient following control strategy based on …

This article proposes a novel identification framework for estimating the parameters of the
controlled autoregressive autoregressive moving average (CARARMA) models with colored …

Parameter estimation is the basis of adaptive control for dynamic systems. This paper
surveys and reviews some parameter estimation methods, including the projection …