Please use this identifier to cite or link to this item: https://scholarbank.nus.edu.sg/handle/10635/230691
Title: ADVANCED MODELLING OF GaAs HBTs AND GaN HEMTs FOR RF APPLICATIONS
Authors: HU WENRUI
ORCID iD:   orcid.org/0000-0001-5514-4130
Keywords: Artificial neural network, large-signal modeling, self-heating effects, small-signal parameter extraction, trapping effects
Issue Date: 19-Apr-2022
Citation: HU WENRUI (2022-04-19). ADVANCED MODELLING OF GaAs HBTs AND GaN HEMTs FOR RF APPLICATIONS. ScholarBank@NUS Repository.
Abstract: Accurate models for RF/microwave transistors are essential for circuit design using electronic design automation tools. Many empirical and artificial neural network (ANN)-based models have been developed. However, empirical models are becoming increasingly complex to capture thermal effects. ANN-based modelling is sensitive to outliers, and some ANN-based models are not charge-conservative. In addition, ANN architecture is determined by a trial-and-error process. This thesis presents the small- and large-signal modelling of gallium arsenide (GaAs) heterojunction bipolar transistors (HBTs) and gallium nitride (GaN) high electron mobility transistors (HEMTs). Measurement data are obtained for model development and verification. Firstly, a dimension reduction method is investigated for fast temperature-dependent current modelling. Secondly, hybrid extraction and outlier detection are developed to obtain reliable datasets for accurate ANN-based modelling. Furthermore, an ANN-based consistent gate charge model is proposed. Lastly, an evolutionary multilayer perceptron-based modelling approach is proposed to construct an accurate model with a proper architecture.
URI: https://scholarbank.nus.edu.sg/handle/10635/230691
Appears in Collections:Ph.D Theses (Open)

Show full item record
Files in This Item:
File Description SizeFormatAccess SettingsVersion 
HuWR.pdf9.84 MBAdobe PDF

OPEN

NoneView/Download

Page view(s)

46
checked on Nov 17, 2022

Download(s)

7
checked on Nov 17, 2022

Google ScholarTM

Check


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.