A review on the design and optimization of antennas using machine learning algorithms and techniques
HM El Misilmani, T Naous… - International Journal of …, 2020 - Wiley Online Library
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 …
learning (ML) in antenna design and optimization. An overview of the conventional …
Application of machine learning in electromagnetics: Mini-review
As an integral part of the electromagnetic system, antennas are becoming more advanced
and versatile than ever before, thus making it necessary to adopt new techniques to …
and versatile than ever before, thus making it necessary to adopt new techniques to …
An intelligent antenna synthesis method based on machine learning
D Shi, C Lian, K Cui, Y Chen… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
An intelligent antenna synthesis method is proposed to automatically select suitable
antenna type and provide optimal geometric parameters according to the requirement of …
antenna type and provide optimal geometric parameters according to the requirement of …
Deep neural network-based automatic metasurface design with a wide frequency range
Beyond the scope of conventional metasurface, which necessitates plenty of computational
resources and time, an inverse design approach using machine learning algorithms …
resources and time, an inverse design approach using machine learning algorithms …
Circularly polarized printed dual port MIMO antenna with polarization diversity optimized by machine learning approach for 5G NR n77/n78 frequency band …
In this communication, a planar dual port multiple input multiple output antenna of size 1.2
λ0× 0.6 λ0× 0.008 λ0 with LHCP/RHCP features is reported for the fifth-generation new radio …
λ0× 0.6 λ0× 0.008 λ0 with LHCP/RHCP features is reported for the fifth-generation new radio …
Efficient modelling of compact microstrip antenna using machine learning
In this article, an application of regression-based machine learning (ML) approaches to
compute resonant frequency at dominant mode TM 10, slot dimensions of square patch, and …
compute resonant frequency at dominant mode TM 10, slot dimensions of square patch, and …
Deep learning assisted fractal slotted substrate MIMO antenna with characteristic mode analysis (CMA) for Sub-6 GHz n78 5 G NR applications: design, optimization …
This article presents the design and optimization of a Deep Learning assisted MIMO
antenna for 5 G New Radio (NR) applications in Sub-6 GHz band. The Prototype of the …
antenna for 5 G New Radio (NR) applications in Sub-6 GHz band. The Prototype of the …
[PDF][PDF] Ultra-wideband CPW fed band-notched monopole antenna optimization using machine learning
In this article, a compact Coplanar Waveguide (CPW) fed band-notched monopole antenna
is designed and optimized. The unique feature of this article is to provide an approach for …
is designed and optimized. The unique feature of this article is to provide an approach for …
Knowledge-guided active-base-element modeling in machine-learning-assisted antenna-array design
Machine-learning (ML)-assisted antenna-array design methods suffer from a heavy
computational burden. In this article, a knowledge-guided active-base-element-modeling …
computational burden. In this article, a knowledge-guided active-base-element-modeling …
Generalized formulation of response features for reliable optimization of antenna input characteristics
A Pietrenko-Dabrowska, S Koziel - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Electromagnetic (EM)-driven parameter adjustment has become imperative in the design of
modern antennas. It is necessary because the initial designs rendered through topology …
modern antennas. It is necessary because the initial designs rendered through topology …