Recent Advances in Physics-Driven Machine Learning Approaches to Intelligent Design of Metasurfaces-Reference-Cited by-同舟云学术

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Recent Advances in Physics-Driven Machine Learning Approaches to Intelligent Design of Metasurfaces

Published:2023-07-03 Issue: Volume: Page:
ISSN:
Container-title:2023 Photonics & Electromagnetics Research Symposium (PIERS)
language:
Short-container-title:

Author:

Lin Xiumei¹,Hou Junming¹,Zhang Jianan¹,You Jian Wei¹,Cui Tie Jun¹

Affiliation:

1. Southeast University,State Key Laboratory of Millimeter Waves,Nanjing,China

Funder

Natural Science Foundation of Jiangsu Province

Fundamental Research Funds for the Central Universities

National Natural Science Foundation of China

National Key Research and Development Program of China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10221213/10220948/10221424.pdf?arnumber=10221424

Reference11 articles.

1. Parameterized Modeling Incorporating MOR-Based Rational Transfer Functions With Neural Networks for Microwave Components

2. Adaptive Feature Zero Assisted Surrogate-Based EM Optimization for Microwave Filter Design

3. Superradiant absorption in multiple optical nanoresonators

4. Four-wave mixing of topological edge plasmons in graphene metasurfaces

5. Accurate Analysis of Finite-Volume Lumped Elements in Metamaterial Absorber Design

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