5 papers
Cross-Material Support Transfer for Core-Loss Prediction Under Waveform Covariate Shift
Cong Yao, Chunye Gong
Power magnetic materials are characterized on the sinusoidal and triangular waveforms that excitation hardware conveniently produces, whereas deployed converters expose cores to tr…
CAHR-Net: Condition-Adaptive Hysteresis Reconstruction for Compact and Interpretable Magnetic Core Loss Modeling
Chunye Gong, Cong Yao
Magnetic core loss originates in the hysteresis loop: the energy dissipated per excitation cycle equals the loop area, and frequency, temperature, and waveform shape set the loss b…
Spectral entropy prior-guided deep feature fusion architecture for magnetic core loss
Cong Yao, Chunye Gong, Jin Zhang
Accurate core loss modeling is critical for the design of high-efficiency power electronic systems. Traditional core loss modeling methods have limitations in prediction accuracy.…
Fine-Grained Vectorized Merge Sorting on RISC-V: From Register to Cache
Jin Zhang, Jincheng Zhou, Xiang Zhang +2
Merge sort as a divide-sort-merge paradigm has been widely applied in computer science fields. As modern reduced instruction set computing architectures like the fifth generation (…
A Hybrid Vectorized Merge Sort on ARM NEON
Jincheng Zhou, Jin Zhang, Xiang Zhang +3
Sorting algorithms are the most extensively researched topics in computer science and serve for numerous practical applications. Although various sorts have been proposed for effic…