Deep Learning based Modeling and Inverse Design for Arbitrary Planar Antenna Structures at RF and Millimeter-Wave
Author:
Affiliation:
1. Princeton University,Dept. of Electrical and Computer Engineering,Princeton,NJ,USA,08544
2. IIT Madras,Dept. of Electrical Engineering,Chennai,India,600036
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9886005/9885799/09887077.pdf?arnumber=9887077
Reference3 articles.
1. Machine Learning Techniques for Optimizing Design of Double T-Shaped Monopole Antenna
2. Multistage Collaborative Machine Learning and its Application to Antenna Modeling and Optimization
3. Antenna Preprocessing and Element-Pattern Shaping for Multi-Band mmWave Arrays: Multi-Port Receivers and Antennas
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1. IMS Deep Learning Enabled Generalized Synthesis of Multi-Port Electromagnetic Structures and Circuits for mmWave Power Amplifiers;2024 IEEE/MTT-S International Microwave Symposium - IMS 2024;2024-06-16
2. A Spatial Inverse Design Method (SIDM) Based on Machine Learning for Frequency-Selective-Surface (FSS) Structures;IEEE Transactions on Antennas and Propagation;2024-03
3. Deep-Learning-Based Inverse-Designed Millimeter-Wave Passives and Power Amplifiers;IEEE Journal of Solid-State Circuits;2023-11
4. Tandem Neural Network Based Design of Multiband Antennas;IEEE Transactions on Antennas and Propagation;2023-08
5. Inverse design of multiparameter antenna using hybrid machine learning‐driven training dataset;Microwave and Optical Technology Letters;2023-04-16
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