HARDCORE: H-field and power loss estimation for arbitrary waveforms with residual, dilated convolutional neural networks in ferrite cores

Documenti analoghi

• RHINO-MAG: Recursive H-Field Inference based on Observed Magnetic Flux under Dynamic Excitation
  di: Vater, Hendrik, et al.
  Pubblicazione: (2026)
• A Power Electronic Converter Control Framework Based on Graph Neural Networks -- An Early Proof-of-Concept
  di: Jakobeit, Darius, et al.
  Pubblicazione: (2026)
• Grease the gears for a steady microfluidic flow
  di: Leuthner, Moritz, et al.
  Pubblicazione: (2023)
• Metasurface-based all-optical diffractive convolutional neural networks
  di: Liang, Zhijiang, et al.
  Pubblicazione: (2025)
• Magnetic field estimation using Gaussian process regression for interactive wireless power system design
  di: Honjo, Yuichi, et al.
  Pubblicazione: (2025)