In the past few decades, circuits based on gallium nitride high electron mobility transistor
(GaN HEMT) have demonstrated exceptional potential in a wide range of high-power and …

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 …

This article proposes a receiver position estimation method suitable for multitransmitter
(multi-TX) wireless power transfer systems from a new perspective of machine learning. The …

The distributed nature of power electronic components parameters can affect the desired
output voltage of the CLLC-type dual active bridge (DAB) converters, especially in mass …

This paper explores and develops efficient temperature‐dependent small‐signal modeling
approaches for GaN high electron mobility transistors (HEMTs). The multilayer perceptron …

Neural networks are widely used to build large-signal models; an appropriate network
architecture is important for high model accuracy and good generalization ability. In this …

Abstract The Genetic Algorithm-Extreme Learning Machine (GA-ELM) neural network
algorithm is proposed to model the relevant characteristics of GaN pseudomorphic high …

This article presents accurate, efficient and reliable small-signal model parameter extraction
approaches applied to Gallium Nitride (GaN) High Electron Mobility Transistor (HEMT) …

A variety of novel behavioral modeling techniques have been reported to accurately capture
the nonlinear characteristics of GaN devices. For the purpose of describing GaN HEMT large …

This paper presents an investigation into the modeling of Gallium Nitride (GaN) High
Electron Mobility Transistors (HEMTs) using multiple Machine Learning (ML) algorithms …