A new and Reliable Decision Tree Based Small-Signal Behavioral Modeling of GaN HEMT

Ahmad Khusro, Mohammad Hashmi, Abdul Quaiyum Ansari, Medet Auyenur

2019

Closed access Metadata (CSL-JSON)
DOI 10.1109/mwscas.2019.8885334
Data confidence 70 medium
How this score is calculated

It is built from checkable properties of the record itself: whether the article has a DOI, how many independent sources confirmed its data, whether the required fields are filled in, and how recent the latest confirmation is. Disagreement between sources and a missing identifier lower it. A value of 80 or above means the record was published without further checking; 60 to 79 means it is published at reduced confidence, with a manual check advisable. A record verified by an editor by hand is never pushed below 90 by a recalculation. This scores our data about the article, not the article itself.

Abstract

The paper, for the first time, explores multivariable small signal modeling technique of GaN HEMT based on Decision tree. The proposed model presents a novel binary decision tree to model the GaN HEMT device for multi-biasing and broad frequency range. Bayesian algorithm has been used to find the optimal hyperparameters for better generalization capability and higher accuracy. An excellent agreement is found between the measured S-parameters and the proposed model for complete frequency range of 1GHz-18GHz.