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

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

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...

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Bibliographic Details
Main Authors: Li, Haolin, Liu, Shuo, Tan, Eng Leong
Other Authors: School of Electrical and Electronic Engineering
Format: Journal Article
Language:English
Published: 2025
Subjects:
Engineering
Coarse-fine grid reconstruction
Deep learning network
Online Access:https://hdl.handle.net/10356/182288

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