This paper presents a focused and comprehensive literature survey on the use of machine learning (ML) in antenna design and optimization. An overview of the conventional …
J Wang, YH Kim, J Ryu, C Jeong… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
The artificial neural network (ANN)-based compact modeling methodology is evaluated in the context of advanced field-effect transistor (FET) modeling for Design-Technology …
J Jin, C Zhang, F Feng, W Na, J Ma… - IEEE Transactions on …, 2019 - ieeexplore.ieee.org
This article introduces the deep neural network method into the field of high-dimensional microwave modeling. Deep learning is nowadays highly successful in solving complex and …
We review the space-mapping (SM) technique and the SM-based surrogate (modeling) concept and their applications in engineering design optimization. For the first time, we …
Neural-network computational modules have recently gained recognition as an unconventional and useful tool for RF and microwave modeling and design. Neural …
C Zhang, J Jin, W Na, QJ Zhang… - IEEE Transactions on …, 2018 - ieeexplore.ieee.org
This paper presents a new technique for artificial neural network (ANN) inverse modeling and applications to microwave filters. In inverse modeling of a microwave component, the …
Antenna Theory and Microstrip Antennas offers a uniquely balanced analysis of antenna fundamentals and microstrip antennas. Concise and readable, it provides theoretical …
F Feng, C Zhang, J Ma, QJ Zhang - IEEE Transactions on …, 2015 - ieeexplore.ieee.org
This paper proposes an advanced technique to develop combined neural network and pole- residue-based transfer function models for parametric modeling of electromagnetic (EM) …
JE Rayas-Sánchez - IEEE Transactions on Microwave Theory …, 2004 - ieeexplore.ieee.org
This paper reviews the current state-of-the-art in electromagnetic (EM)-based design and optimization of microwave circuits using artificial neural networks (ANNs). Measurement …