Super-resolution deep learning network for finite-difference time-domain simulations

• المؤلفون الرئيسيون: Li, Haolin, Liu, Shuo, Tan, Eng Leong
• مؤلفون آخرون: School of Electrical and Electronic Engineering
• التنسيق: مقال
• اللغة: English
• منشور في: 2025
• الموضوعات: Engineering; Coarse-fine grid reconstruction; Deep learning network
• الوصول للمادة أونلاين: https://hdl.handle.net/10356/182288

When selecting the spatial grid size in finite-difference time-domain (FDTD) simulations, it is necessary to balance numerical dispersion and computational resources. Coarser grids are less computationally intensive but decrease simulation accuracy, while finer grids can reduce numerical dispersion...