InP HBT Small Signal Modeling based on Artificial Neural Network for Millimeter-wave Application

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

4 Scopus citations

Abstract

InP heterojunction bipolar transistor (HBT) small signal modeling technique based on artificial neural network(ANN) is proposed in this paper. Two ANN models with different outputs form are given and compared. In the frequency range of 2-110 GHz, good agreements between the measured and model-calculated data can be achieved to demonstrate that the ANN model outputs with complex numbers form is more accurate than amplitude-phase form.

Original languageEnglish
Title of host publication2020 IEEE MTT-S International Conference on Numerical Electromagnetic and Multiphysics Modeling and Optimization, NEMO 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728169668
DOIs
StatePublished - 7 Dec 2020
Event2020 IEEE MTT-S International Conference on Numerical Electromagnetic and Multiphysics Modeling and Optimization, NEMO 2020 - Hangzhou, China
Duration: 7 Dec 20209 Dec 2020

Publication series

Name2020 IEEE MTT-S International Conference on Numerical Electromagnetic and Multiphysics Modeling and Optimization, NEMO 2020

Conference

Conference2020 IEEE MTT-S International Conference on Numerical Electromagnetic and Multiphysics Modeling and Optimization, NEMO 2020
Country/TerritoryChina
CityHangzhou
Period7/12/209/12/20

Keywords

  • artificial neural network (ANN)
  • heterojunction bipolar transistor (HBT)
  • small signal model

Fingerprint

Dive into the research topics of 'InP HBT Small Signal Modeling based on Artificial Neural Network for Millimeter-wave Application'. Together they form a unique fingerprint.

Cite this