Accelerate Electromagnetic Scattering Computation with LSTM Neural Networks-Reference-Cited by-同舟云学术

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Accelerate Electromagnetic Scattering Computation with LSTM Neural Networks

Published:2023-10-20 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE 7th International Symposium on Electromagnetic Compatibility (ISEMC)
language:
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Author:

Yang Yuanpeng¹,Wang Qingyao¹,Xinyang Shi²,Bo Luo³,Fang Chonghua¹

Affiliation:

1. China Ship Development and Design Centre,Science and Technology on Electromagnetic Compatibility Laboratory,Wuhan,China

2. Research Institute,Wuhan Maritime Communication,Wuhan,China

3. Changjiang Polytechnic,Electromechanical Automobile Academy,Wuhan,China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10370006/10368602/10370206.pdf?arnumber=10370206

Reference14 articles.

1. Physics Embedded Deep Neural Network for Solving Volume Integral Equation: 2D Case

2. Enhanced PML Based on the Long Short Term Memory Network for the FDTD Method

3. RCS Optimization of Surface Geometry With Physics Inspired Neural Networks

4. A MLP Based FDTD Method

5. Fast Computation by MLFMM-FFT with NURBS in Large Volumetric Dielectric Structures

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