Deep learning (DL) has been widely used in various fields. However, its black-box nature
limits people's understanding and trust in its decision-making process. Therefore, it becomes …

This article considers the iterative identification problems for a class of feedback nonlinear
systems with moving average noise. The model contains both the dynamic linear module …

Saturation nonlinearity exists widely in various practical control systems. Modeling and
parameter estimation of systems with saturation nonlinearity are of great importance for …

In industrial process control systems, parameter estimation is crucial for controller design
and model analysis. This article examines the issue of identifying parameters in continuous …

It is essential for meeting the stringent real-time demands encountered in actual production
scenarios. Employing the low computational complexity of recursive algorithms, some new …

The primary focus of this article is to explore parameter estimation for time-varying systems
affected by colored noise. Based on the attributes of the time-varying system with colored …

This study proposes a filtering based maximum likelihood generalized extended gradient
algorithm for multivariable nonlinear systems with autoregressive moving average noises …

Multi-object tracking (MOT) tasks face challenges from multiple perception views due to the
diversity of application scenarios. Different views (front-view and top-view) have different …

Through dividing a multivariable system into several subsystems, this paper derives the sub‐
identification model. Utilizing the obtained sub‐identification model, an auxiliary model …