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Accurate Modeling of Antenna Structures by Means of Domain Confinement and Pyramidal Deep Neural Networks
(Institute of Electrical and Electronics Engineers Inc., 2022)
The importance of surrogate modeling techniques has been gradually increasing in the design of antenna structures over the recent years. Perhaps the most important reason is a high cost of full-wave electromagnetic (EM) ...
Rapid Design of 3D Reflectarray Antennas by Inverse Surrogate Modeling and Regularization
(Institute of Electrical and Electronics Engineers Inc., 2023)
Reflectarrays (RAs) exhibit important advantages over conventional antenna arrays, especially in terms of realizing pencil-beam patterns without the employment of the feeding networks. Unfortunately, microstrip RA ...
Low-Cost and Highly Accurate Behavioral Modeling of Antenna Structures by Means of Knowledge-Based Domain-Constrained Deep Learning Surrogates
(Institute of Electrical and Electronics Engineers Inc., 2023)
The awareness and practical benefits of behavioral modeling methods have been steadily growing in the antenna engineering community over the last decade or so. Undoubtedly, the most important advantage thereof is a possibility ...
Optimal design of transmitarray antennas via low-cost surrogate modelling
(Nature Research, 2023)
Over the recent years, reflectarrays and transmitarrays have been drawing a considerable attention due to their attractive features, including a possibility of realizing high gain and pencil-like radiation patterns without ...
Deep-learning-based precise characterization of microwave transistors using fully-automated regression surrogates
(Nature Research, 2023)
Accurate models of scattering and noise parameters of transistors are instrumental in facilitating design procedures of microwave devices such as low-noise amplifiers. Yet, data-driven modeling of transistors is a challenging ...