2023 APS Logo

IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting

July 23–28, 2023 • Portland, Oregon, USA

23-28 July 2023 • Portland, Oregon, USA

IEEE AP-S/URSI 2023

23-28 July 2023 • Portland, Oregon, USA

WE-A1.3P.6

A Fast Radiation Performance Prediction Method for Reconfigurable Transmitarray Based on BP Neural Network

Mengkai Xi, Luyu Zhao, Xidian University, China
Session:
Wideband and Multiband Reconfigurable Antennas
Track:
AP-S: Antennas
Location:
A 107-109 (OCC)
Session Time:
Wed, 26 Jul, 13:20 - 17:00 PDT (UTC -7)
Presentation Time:
Wed, 26 Jul, 15:20 - 15:40 PDT (UTC -7)
Session Co-Chairs:
Xun Gong, University of Central Florida and Mei Song Tong, Tongji University
Presentation
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Discussion
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Session WE-A1.3P
WE-A1.3P.1: A Switched-Beam Yagi-Uda Antenna Array for Dual Channel mm-Wave Communications
Ectis Velazquez, Murat Yuksel, Xun Gong, University of Central Florida, United States
WE-A1.3P.2: Beam Steering Leaky Wave Antenna using Capacitive Loading
Shahinshah Ali, Lakehead University, Canada; Hammad Cheema, National University of Sciences and Technology (NUST), Pakistan; Farhan Ghaffar, Lakehead University, Canada
WE-A1.3P.3: Mechanically Reconfigurable Multi-band Antenna on a 3D-printed Substrate for C/X Band Applications
Karen N. Olan Nuñez, Héctor N. Morales Lovera, Roberto S. Murphy Arteaga, INAOE, Mexico
WE-A1.3P.4: Performance Improvement of Wideband Reconfigurable Planar Antennas
Abdullah Eroglu, Jyosri M Karra, North Carolina A&T State University, United States
WE-A1.3P.5: A Miniaturized Tunable Programmable Reflective Metasurface Unit Based on Minkowski Fractal Geometry
Hao Zheng Lu, Zhen Wang, Xiao Yu Li, Mei Song Tong, Tongji University, China
WE-A1.3P.6: A Fast Radiation Performance Prediction Method for Reconfigurable Transmitarray Based on BP Neural Network
Mengkai Xi, Luyu Zhao, Xidian University, China
Resources
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