A comprehensive overview of the temperature-dependent modeling of the high-power GaN HEMT technology using mm-wave scattering parameter measurements

G Crupi, M Latino, G Gugliandolo, Z Marinković, J Cai… - Electronics, 2023 - mdpi.com
The gallium-nitride (GaN) high electron-mobility transistor (HEMT) technology has emerged
as an attractive candidate for high-frequency, high-power, and high-temperature …

Comprehensive investigation and comparative analysis of machine learning-based small-signal modelling techniques for GaN HEMTs

S Husain, M Hashmi… - IEEE Journal of the …, 2022 - ieeexplore.ieee.org
A number of machine learning (ML) algorithm based small signal modeling of Gallium
Nitride (GaN) High Electron Mobility Transistors (HEMTs) have been reported in literature …

On efficient modeling of drain current for designing high-power GaN HEMT-based circuits

A Jarndal, FR Rakib, MA Alim - Journal of Computational Electronics, 2024 - Springer
In this paper, different modeling approaches to the drain current, including analytical and
artificial neural network (ANN) modeling, are investigated. The adopted models address the …

Accurate, Efficient and Reliable Small-Signal Modelling Approaches for GaN HEMTs

S Husain, A Jarndal, M Hashmi, FM Ghannouchi - IEEE Access, 2023 - ieeexplore.ieee.org
This article presents accurate, efficient and reliable small-signal model parameter extraction
approaches applied to Gallium Nitride (GaN) High Electron Mobility Transistor (HEMT) …

An ASM-HEMT for Large-Signal Modeling of GaN HEMTs in High-Temperature Applications

NC Miller, A Brown, M Elliott, R Gilbert… - IEEE Journal of the …, 2023 - ieeexplore.ieee.org
This paper reports a temperature-dependent ASM-HEMT for modeling GaN HEMTs at
elevated temperatures. Modifications to the standard ASM-HEMT were developed to …

Evaluating Nine Machine Learning Algorithms for GaN HEMT Small Signal Behavioral Modeling through K-fold Cross-Validation

N Ahmad, V Nath - Engineering, Technology & Applied Science …, 2024 - etasr.com
This paper presents an investigation into the modeling of Gallium Nitride (GaN) High
Electron Mobility Transistors (HEMTs) using multiple Machine Learning (ML) algorithms …

Analysis and modeling of the kink effect in S22 based on support vector machine for GaN HEMTs

Z Zhu, M Geng, J Cai, H Gao - International Journal of …, 2022 - Wiley Online Library
In this work, the kink effect (KE), typically visible in S22, is analyzed and modeled. Two
different modeling techniques: equivalent circuit modeling (ECM) method and machine …

Multilayer perceptron–random forest based hybrid machine learning–neural network model for GaN high electron mobility transistor's parameter estimations

A Mishra, S Raut, K Sehra, RP Singh… - … Journal of RF and …, 2022 - Wiley Online Library
This work presents an accurate, scalable, and efficient hybrid machine learning (ML) and
neural network (NN) model based, cross‐platform application to analyze and estimate …

Auto‐encoder based hybrid machine learning model for microwave scaled GaAs pHEMT devices

G Bhargava, V Vadalà, S Majumdar… - International Journal of …, 2022 - Wiley Online Library
In this article, a study of performing machine learning (ML) based modeling for
semiconductor devices has been developed using experimental microwave data …

Comprehensive Investigation of ANN Algorithms Implemented in MATLAB, Python and R for Small-Signal Behavioral Modeling of GaN HEMTs

S Husain, B Kadirbay, A Jarndal… - IEEE Journal of the …, 2023 - ieeexplore.ieee.org
Artificial Neural Network (ANN) is frequently utilized for the development of behavioral
models of Gallium Nitride (GaN) High Electron Mobility Transistors (HEMTs). However …