Identification of Discrete Non-Linear Dynamics of a Radio-Frequency Power Amplifier Circuit using Symbolic Regression.

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

Abstract

The identification of non-linearities or undesirable dynamic behavior of electrical components is a common problem. Previous modeling forms are largely based on extensive physical knowledge at the semiconductor level, which has produced reliable solutions over the past decades. This however implies the measurement of physical prototypes in laboratories, which can be costly. It is therefore desirable to have reliable software models of the prototypes available to outsource this procedure to simulators. This paper presents a number of solutions from the field of empirical modeling including symbolic regression, which allow to parameterize such models from measured values. As an example we are utilizing time-domain data from a real radio-frequency power amplifier circuit. We compare a Hammerstein-Wiener model with two methods for symbolic regression, and find that the Hammerstein-Wiener model produces the best predictions but has many non-zero coefficients. Both symbolic regression methods produce short linear models with slightly higher prediction error than the HW model.

Original languageEnglish
Title of host publicationProceedings - 2022 24th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing, SYNASC 2022
EditorsBruno Buchberger, Mircea Marin, Viorel Negru, Daniela Zaharie
PublisherIEEE
Pages297-303
Number of pages7
ISBN (Electronic)978-1-6654-6545-8
ISBN (Print)978-1-6654-6546-5
DOIs
Publication statusPublished - 2022

Publication series

NameProceedings - 2022 24th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing, SYNASC 2022

Keywords

  • Genetic Programming
  • Non-Linear System Identification
  • Power Amplifier
  • Sparse Identification
  • Symbolic Regression

Fingerprint

Dive into the research topics of 'Identification of Discrete Non-Linear Dynamics of a Radio-Frequency Power Amplifier Circuit using Symbolic Regression.'. Together they form a unique fingerprint.

Cite this