Design of a Novel Explainable Adversarial Autoencoder Model for the Electromagnetic Analysis of Functional Materials Based on Physics-Informed Learning

Machine learning models have found their applications in solving problems that can traditionally handle ordinary or partial differential equations. The full-wave simulations solve such equations for functional materials in the microwave regime. These simulations heavily rely on the electrical proper...

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Hlavní autoři:	Naina Narang, Greeshma Lingam
Médium:	Artigo
Jazyk:	Inglês
Vydáno:	IEEE 2024-01-01
Edice:	IEEE Access
Témata:	Dielectric measurements electromagnetic materials generative adversarial networks physics-informed learning reflection loss Riccati
On-line přístup:	https://ieeexplore.ieee.org/document/10750167/
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