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

Artificial Neural Network (ANN) is frequently utilized for the development of behavioral
models of Gallium Nitride (GaN) High Electron Mobility Transistors (HEMTs). However …

In this paper, a novel technology named Pelican-Gaussian process regression machine
learning algorithm is proposed for modelling the large-signal characteristics of Gallium …

XGBoost is the optimization of gradient boosting with the best overall performance among
machine learning algorithms. By introducing a regularization term into the loss function of …

Support vector machine (SVR) has been introduced into the modeling of S‐parameters in
radio‐frequency (RF) power amplifiers (PA). The modeling accuracy and speed of SVR are …

This paper develops and demonstrates an accurate and effective approach for small-signal
modeling of Gallium Nitride (GaN) High Electron Mobility Transistor (HEMT) using Adaptive …

A systematic optimization of parameters related with Artificial Neural Network (ANN) is
absolutely necessary to extract the best possible optimized ANN, therefore gaining traction …

The accuracy and convergence of Artificial Neural Network (ANN) based models are
contingent on initial weights as they employ backpropagation algorithm. To address these …

This paper compares the performance of the Adaptive Neuro-Fuzzy Interface System
(ANFIS) and Artificial Neural Network (ANN) by developing small-signal models for Gallium …

This paper proposes a globally optimized behavioral modeling algorithm using cascaded
feed-forward neural network in conjugation with Particle Swarm optimization (PSO) for fully …