10-15 July 2022 • Denver, Colorado, USA

IEEE AP-S/URSI 2022

10-15 July 2022 • Denver, Colorado, USA

TH-A3.2P.2

Machine-Learning-Based Deep-Sub-Wavelength Metrology with Uncertainty Quantification

Yanan Liu, Lynford L. Goddard, Jian-Ming Jin, University of Illinois at Urbana-Champaign, United States; Jinlong Zhu, Huazhong University of Science and Technology, China
Session:
Macromodeling and Optimization Methods
Track:
AP-S: Computational & Numerical Techniques
Location:
Capitol Ballroom 5 (HR)
Presentation Time:
Thu, 14 Jul, 13:40 - 14:00 Denver Time (UTC -6)
Session Co-Chairs:
Gaeron Friedrichs, University of Colorado Boulder and Sawyer D. Campbell, The Pennsylvania State University
Presentation
Discussion
Session TH-A3.2P
TH-A3.2P.1: An Augmented Y-parameter Method for Macromodeling Electromagnetic Structures in the Presence of Plane-Waves
Arkaprovo Das, Sawyer D. Campbell, Douglas H. Werner, The Pennsylvania State University, United States
TH-A3.2P.2: Machine-Learning-Based Deep-Sub-Wavelength Metrology with Uncertainty Quantification
Yanan Liu, Lynford L. Goddard, Jian-Ming Jin, University of Illinois at Urbana-Champaign, United States; Jinlong Zhu, Huazhong University of Science and Technology, China
TH-A3.2P.3: Machine Learning Augmentation of Wideband Spectrum Sensors for Polarimetry
Gaeron Friedrichs, Mohamed Elmansouri, Dejan Filipovic, University of Colorado Boulder, United States
TH-A3.2P.4: Expansion in Exponential Sums with Application to Discrete Complex Image Theory
David Tonn, Naval Undersea Warfare Center, Newport, United States; Bourama Toni, Howard University, United States
TH-A3.2P.5: Surrogate Modeling for Designing and Optimizing MIMO Antennas
Lida Kouahlvandi, Dogus, Turkey; Ladislau Matekovits, Politecnico di Torino, Italy
Resources
No resources available.