Unit-free theorem pinpoints key variables for AI and physics models

Machine learning models are designed to take in data, to find patterns or relationships within those data, and to use what ...
IEEE

A Fixed-Time Proximal Gradient Neurodynamic Network With Time-Varying Coefficients for Composite Optimization Problems and Sparse Optimization Problems With Log-Sum Function

Abstract: This article presents a novel proximal gradient neurodynamic network (PGNN) for solving composite optimization problems (COPs). The proposed PGNN with time-varying coefficients can be ...
IEEE

Semi-Heterogeneous Graph-Perception Network With Gradient-Weighted Class Activation Mapping for Class-Incremental Industrial Fault Recognition and Root Cause Diagnosis

Abstract: Modern industrial systems often operate under complex dynamics and strict reliability constraints, demanding a timely and precise fault diagnosis with efficient root cause analysis to ensure ...