Deep neural networks for the evaluation and design of photonic devices

J Jiang, M Chen, JA Fan - Nature Reviews Materials, 2021 - nature.com
The data-science revolution is poised to transform the way photonic systems are simulated
and designed. Photonic systems are, in many ways, an ideal substrate for machine learning …

Deep learning for the design of photonic structures

W Ma, Z Liu, ZA Kudyshev, A Boltasseva, W Cai… - Nature Photonics, 2021 - nature.com
Innovative approaches and tools play an important role in shaping design, characterization
and optimization for the field of photonics. As a subset of machine learning that learns …

Weighting factor design in model predictive control of power electronic converters: An artificial neural network approach

T Dragičević, M Novak - IEEE Transactions on Industrial …, 2018 - ieeexplore.ieee.org
This paper proposes the use of an artificial neural network (ANN) for solving one of the
ongoing research challenges in finite set-model predictive control (FSMPC) of power …

Artificial neural networks for microwave computer-aided design: The state of the art

F Feng, W Na, J Jin, J Zhang, W Zhang… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
This article presents an overview of artificial neural network (ANN) techniques for a
microwave computer-aided design (CAD). ANN-based techniques are becoming useful for …

[HTML][HTML] Advances in Integrated System Health Management for mission-essential and safety-critical aerospace applications

K Ranasinghe, R Sabatini, A Gardi, S Bijjahalli… - Progress in Aerospace …, 2022 - Elsevier
Abstract Integrated System Health Management (ISHM) is a promising technology that fuses
sensor data and historical state-of-health information of components and subsystems to …

[HTML][HTML] Modelling, prediction and classification of student academic performance using artificial neural networks

ET Lau, L Sun, Q Yang - SN Applied Sciences, 2019 - Springer
The conventional statistical evaluations are limited in providing good predictions of the
university educational quality. This paper presents an approach with both conventional …

Machine learning and deep learning in phononic crystals and metamaterials–A review

J Kennedy, CW Lim - Materials Today Communications, 2022 - Elsevier
Abstract Machine learning (ML), as a component of artificial intelligence, encourages
structural design exploration which leads to new technological advancements. By …

Deep neural network technique for high-dimensional microwave modeling and applications to parameter extraction of microwave filters

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 …

Wireless power transfer for future networks: Signal processing, machine learning, computing, and sensing

B Clerckx, K Huang, LR Varshney… - IEEE Journal of …, 2021 - ieeexplore.ieee.org
Wireless power transfer (WPT) is an emerging paradigm that will enable using wireless to its
full potential in future networks, not only to convey information but also to deliver energy …

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 …