TH-A6.3P.8

On deep learning based beam selection in the presence of array imperfections

Jayakrishnan Vijayamohanan, Arjun Gupta, Christos Christodoulou, The University of New Mexico, United States
Session:
Novel Approaches in the Design of Antennas using AI Oral
Track:
AP-S: Antenna Applications and Emerging Technologies
Location:
Spadolini: 1-07
Session Time:
Thu, 18 Jul, 13:40 - 17:20
Presentation Time:
Thu, 18 Jul, 16:20 - 16:40
Session Chair:
Vishwanath Iyer, MathWorks Inc.
Presentation
Discussion
Session TH-A6.3P
TH-A6.3P.1: AI-Based 3D Antenna Pattern Reconstruction
Peter J. DiMeo, Sudarshan Sivaramakrishnan, Vishwanath Iyer, The MathWorks Inc., United States
TH-A6.3P.2: A Multi-resolution Adaptive Encoding Method for 3-D Reconstruction of DPO-SDF
Yanpeng Jia, Yuxuan Li, Ce Ding, Lizhen Yang, Hai Lin, ZheJiang University, China
TH-A6.3P.3: Fabry Perot Array Antenna Design Using Machine Learning
Mohammed Farouk Nakmouche, Dominic Deslandes, Ghyslain Gagnon, Ecole de technologie superieure, Canada; George Xiao, Jianping Lu, National Research Council, Canada
TH-A6.3P.4: Non-Destructive Fabrication Fault Detection in Electromagnetic Designs using Machine Learning
Ravi Kumar Arya, Zhongshan Institute of Changchun University of Science and Technology, China; Aswin Chowdary, Washington University in St. Louis, United States; Pawan Kumar, Calibyte Private Limited, India; Raj Mittra, University of Central Florida, United States; Guangyi Ai, Junwei Dong, Zhongshan Institute of Changchun University of Science and Technology, China
TH-A6.3P.7: Diagnosis of Array Antennas Element Faults Based on R-CNN Using Near-Field Data
Boguang Yang, Licheng Yang, Tao Hong, Xidian University, China
TH-A6.3P.8: On deep learning based beam selection in the presence of array imperfections
Jayakrishnan Vijayamohanan, Arjun Gupta, Christos Christodoulou, The University of New Mexico, United States
Resources
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