Accurate and Effective Nonlinear Behavioral Modeling of a 10-W GaN HEMT Based on LSTM Neural Networks-Reference-Cited by-同舟云学术

Accurate and Effective Nonlinear Behavioral Modeling of a 10-W GaN HEMT Based on LSTM Neural Networks

Published:2023 Issue: Volume:11 Page:27267-27279
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Geng Mingqiang¹,Crupi Giovanni²^ORCID,Cai Jialin¹^ORCID

Affiliation:

1. Key Laboratory of RF Circuit and System, Ministry of Education, College of Electronics and Information, Hangzhou Dianzi University, Hangzhou, China

2. BIOMORF Department, University of Messina, Messina, Italy

Funder

Provincial Universities of Zhejiang

Qianjiang Talent Project Type-D of Zhejiang

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/10005208/10075428.pdf?arnumber=10075428

Reference51 articles.

1. Assessing GaN FET Performance Degradation in Power Amplifiers for Pulsed Radar Systems

2. A New Dynamic-Bias Measurement Setup for Nonlinear Transistor Model Identification

3. Physics-Oriented Device Model for Packaged GaN Devices

4. Compensation of Long-Term Memory Effects on GaN HEMT-Based Power Amplifiers

5. 2-D Magnitude-Selective Affine Function-Based Digital Predistortion for Concurrent Dual-Band Terminal Power Amplifiers

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