QDRFormer: Quantum-Inspired Density Representation Learning With Random Forest-Guided Transformers for Early Prediction of PLL Instability and Chaos
Early prediction of nonlinear instability in phase-locked loops (PLLs) is essential for ensuring the reliability of modern power electronic and communication systems. This paper presents QDRFormer, a quantum-inspired density representation learning framework integrating density-matrix-based features, local instability...