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0.3 - 1.1GHz互补金属氧化物半导体A类宽带功率放大器温度特性行为的研究与建模

Investigation and Modeling of the Behavior of Temperature Characteristics of 0.3-1.1 GHz Complementary Metal Oxide Semiconductor Class-A Broadband Power Amplifiers.

作者信息

Li Ruiliang, Zhou Shaohua, Yang Cheng, Wang Jian

机构信息

Qingdao Institute for Marine Technology of Tianjin University, Qingdao 266200, China.

ZJU-Hangzhou Global Scientific and Technological Innovation Center, Zhejiang University, Hangzhou 310058, China.

出版信息

Micromachines (Basel). 2024 Feb 6;15(2):246. doi: 10.3390/mi15020246.

DOI:10.3390/mi15020246
PMID:38398973
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10891772/
Abstract

A power amplifier (PA) stands as a central module within the electronic information system (EIS), and any variation in a PA's specifications has a direct impact on the EIS's performance, especially in the face of temperature fluctuations. In examining the influence of PA specification changes on the EIS, we employed support vector machine (SVM) to model the behavior of the temperature characteristics of 0.3-1.1 GHz complementary metal oxide semiconductor (CMOS) class-A broadband PAs. The results show that the parameters of S, S, S, and S can be effectively modeled. SVM outperforms Elman and GRNN in terms of combined modeling time and modeling accuracy. This research can be extended to modeling the behavior of other types of power amplifiers or devices and circuits.

摘要

功率放大器(PA)是电子信息系统(EIS)中的核心模块,PA规格的任何变化都会直接影响EIS的性能,尤其是在面对温度波动时。在研究PA规格变化对EIS的影响时,我们采用支持向量机(SVM)对0.3 - 1.1 GHz互补金属氧化物半导体(CMOS)A类宽带PA的温度特性行为进行建模。结果表明,S、S、S和S参数可以得到有效建模。在组合建模时间和建模精度方面,SVM优于Elman和GRNN。该研究可扩展到对其他类型功率放大器或器件及电路的行为进行建模。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a878/10891772/b0b38ef34bba/micromachines-15-00246-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a878/10891772/72876f443173/micromachines-15-00246-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a878/10891772/5289f3a417fd/micromachines-15-00246-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a878/10891772/55c27e876774/micromachines-15-00246-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a878/10891772/f7cb70f2b310/micromachines-15-00246-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a878/10891772/b0b38ef34bba/micromachines-15-00246-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a878/10891772/72876f443173/micromachines-15-00246-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a878/10891772/5289f3a417fd/micromachines-15-00246-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a878/10891772/55c27e876774/micromachines-15-00246-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a878/10891772/f7cb70f2b310/micromachines-15-00246-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a878/10891772/b0b38ef34bba/micromachines-15-00246-g005.jpg

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