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Toplam kayıt 5, listelenen: 1-5
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 ...
Data-Driven Surrogate-Assisted Optimization of Metamaterial-Based Filtenna Using Deep Learning
(MDPI, 2023)
In this work, a computationally efficient method based on data-driven surrogate models is proposed for the design optimization procedure of a Frequency Selective Surface (FSS)-based filtering antenna (Filtenna). A Filtenna ...
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 ...