Interpretability research of deep learning: A literature survey

B Xua, G Yang - Information Fusion, 2024 - Elsevier
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 …

Auxiliary model maximum likelihood gradient‐based iterative identification for feedback nonlinear systems

L Liu, F Li, J Ma, H Xia - Optimal Control Applications and …, 2024 - Wiley Online Library
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 …

Parameter estimation methods for time‐invariant continuous‐time systems from dynamical discrete output responses based on the Laplace transforms

KA Ibrahim, F Ding - … Journal of Adaptive Control and Signal …, 2024 - Wiley Online Library
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 …

Separable synchronous auxiliary model adaptive momentum estimation strategy for a time-varying system with colored noise from on-line measurements

Y Zhao, Y Ji - ISA transactions, 2024 - Elsevier
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 …

Data Filtering-Based Maximum Likelihood Gradient-Based Iterative Algorithm for Input Nonlinear Box–Jenkins Systems with Saturation Nonlinearity

Y Fan, X Liu, M Li - Circuits, Systems, and Signal Processing, 2024 - Springer
Saturation nonlinearity exists widely in various practical control systems. Modeling and
parameter estimation of systems with saturation nonlinearity are of great importance for …

Gradient-Based Recursive Parameter Estimation Methods for a Class of Time-Varying Systems from Noisy Observations

N Xu, Q Liu, F Ding - Circuits, Systems, and Signal Processing, 2024 - Springer
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 …