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Decision Tree Based Small-Signal Modelling of GaN HEMT and CAD Implementation

  • Nazarbayev University

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Scopus citations

Abstract

This paper explores the use of Decision Tree algorithm in the development of small signal model of GaN HEMT. In this stage, each measured s-parameters are modelled separately exploiting the bias, frequency and geometry dependence of the device as input predictors. This necessitates the tuning of parameters using Bayesian optimization and Random search algorithms. The outcome in terms of MSE and MAE demonstrates that the Random search algorithm gives a superior agreement with the measured values for the entire frequency range. Subsequently, the developed model is incorporated in the commercial CAD environment and a class-F power amplifier is designed to highlight the seamless integration ability and effectiveness of the developed model.

Original languageEnglish
Title of host publication2022 IEEE International Conference on Consumer Electronics, ICCE 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781665441544
DOIs
StatePublished - 2022
Event2022 IEEE International Conference on Consumer Electronics, ICCE 2022 - Virtual, Online, United States
Duration: 7 Jan 20229 Jan 2022

Publication series

NameDigest of Technical Papers - IEEE International Conference on Consumer Electronics
Volume2022-January
ISSN (Print)0747-668X

Conference

Conference2022 IEEE International Conference on Consumer Electronics, ICCE 2022
Country/TerritoryUnited States
CityVirtual, Online
Period7/01/229/01/22

Keywords

  • ADS Implementation
  • Bayesian optimization
  • Decision Tree
  • GaN HEMT
  • Random search algorithm

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