CS-GA-XGBoost-Based Model for a Radio-Frequency Power Amplifier under Different Temperatures
CS-GA-XGBoost-Based Model for a Radio-Frequency Power Amplifier under Different Temperatures
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Publisher
Basel: MDPI AG
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Language
English
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Publisher
Basel: MDPI AG
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Scope and Contents
Contents
Machine learning methods, such as support vector regression (SVR) and gradient boosting, have been introduced into the modeling of power amplifiers and achieved good results. Among various machine learning algorithms, XGBoost has been proven to obtain high-precision models faster with specific parameters. Hyperparameters have a significant impact o...
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Full title
CS-GA-XGBoost-Based Model for a Radio-Frequency Power Amplifier under Different Temperatures
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Record Identifier
TN_cdi_doaj_primary_oai_doaj_org_article_e7c9d231b6f44bf682172398d2f5387e
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_e7c9d231b6f44bf682172398d2f5387e
Other Identifiers
ISSN
2072-666X
E-ISSN
2072-666X
DOI
10.3390/mi14091673
