• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利：CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法，用中文像聊天一样搜索，搜遍4000万医学文献。AI智能推荐，让科研检索更轻松。

立即免费搜索

文件翻译

保留排版，准确专业，支持PDF/Word/PPT等文件格式，支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述，25分钟生成高质量综述，智能提取关键信息，辅助科研写作。

立即免费体验

基于极限学习机的射频放大器关键规格建模

Modeling of Key Specifications for RF Amplifiers Using the Extreme Learning Machine.

作者信息

Zhou Shaohua, Yang Cheng, Wang Jian

机构信息

School of Microelectronics, Tianjin University, Tianjin 300072, China.

Qingdao Institute for Ocean Technology, Tianjin University, Qingdao 266200, China.

出版信息

Micromachines (Basel). 2022 Apr 28;13(5):693. doi: 10.3390/mi13050693.

DOI:10.3390/mi13050693
PMID:35630160
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9148139/
Abstract

The amplifier is a key component of the radio frequency (RF) front-end, and its specifications directly determine the performance of the system in which it is located. Unfortunately, amplifiers' specifications degrade with temperature and even lead to system failure. To study how the system failure is affected by the amplifier specification degradation, it is necessary to couple the amplifier specification degradation into the system optimization design. Furthermore, to couple the amplifier specification degradation into the optimal design of the system, it is necessary to model the characteristics of the amplifier specification change with temperature. In this paper, the temperature characteristics of two amplifiers are modeled using an extreme learning machine (ELM), and the results show that the model agrees well with the measurement results and can effectively reduce measurement time and cost.

摘要

放大器是射频（RF）前端的关键组件，其规格直接决定了它所在系统的性能。不幸的是，放大器的规格会随温度降低，甚至导致系统故障。为了研究系统故障如何受到放大器规格退化的影响，有必要将放大器规格退化纳入系统优化设计中。此外，为了将放大器规格退化纳入系统的优化设计，有必要对放大器规格随温度变化的特性进行建模。本文使用极限学习机（ELM）对两个放大器的温度特性进行建模，结果表明该模型与测量结果吻合良好，能够有效减少测量时间和成本。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eb28/9148139/6f402e901b12/micromachines-13-00693-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eb28/9148139/1b8923dc4981/micromachines-13-00693-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eb28/9148139/647e38c5b856/micromachines-13-00693-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eb28/9148139/37dac46f376d/micromachines-13-00693-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eb28/9148139/9c4b266989bb/micromachines-13-00693-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eb28/9148139/33827bb98bd0/micromachines-13-00693-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eb28/9148139/4e0e3c9ec37c/micromachines-13-00693-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eb28/9148139/f208c2be3ce0/micromachines-13-00693-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eb28/9148139/6f402e901b12/micromachines-13-00693-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eb28/9148139/1b8923dc4981/micromachines-13-00693-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eb28/9148139/647e38c5b856/micromachines-13-00693-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eb28/9148139/37dac46f376d/micromachines-13-00693-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eb28/9148139/9c4b266989bb/micromachines-13-00693-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eb28/9148139/33827bb98bd0/micromachines-13-00693-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eb28/9148139/4e0e3c9ec37c/micromachines-13-00693-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eb28/9148139/f208c2be3ce0/micromachines-13-00693-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eb28/9148139/6f402e901b12/micromachines-13-00693-g008.jpg

相似文献

1
Modeling of Key Specifications for RF Amplifiers Using the Extreme Learning Machine.基于极限学习机的射频放大器关键规格建模
Micromachines (Basel). 2022 Apr 28;13(5):693. doi: 10.3390/mi13050693.
2
Automatic Piecewise Extreme Learning Machine-Based Model for -Parameters of RF Power Amplifier.基于自动分段极限学习机的射频功率放大器参数模型
Micromachines (Basel). 2023 Apr 13;14(4):840. doi: 10.3390/mi14040840.
3
Support Vector Machine-Based Model for 2.5-5.2 GHz CMOS Power Amplifier.基于支持向量机的2.5 - 5.2 GHz CMOS功率放大器模型
Micromachines (Basel). 2022 Jun 27;13(7):1012. doi: 10.3390/mi13071012.
4
Temperature Characteristics Modeling for GaN PA Based on PSO-ELM.基于粒子群优化极限学习机的氮化镓功率放大器温度特性建模
Micromachines (Basel). 2024 Aug 5;15(8):1008. doi: 10.3390/mi15081008.
5
Investigation and Modeling of the Behavior of Temperature Characteristics of 0.3-1.1 GHz Complementary Metal Oxide Semiconductor Class-A Broadband Power Amplifiers.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
Micromachines (Basel). 2024 Feb 6;15(2):246. doi: 10.3390/mi15020246.
6
Multi-Tone Harmonic Balance Optimization for High-Power Amplifiers through Coarse and Fine Models Based on X-Parameters.基于 X 参数的多音谐波平衡优化在大功率放大器中的粗调和细调模型。
Sensors (Basel). 2022 Jun 6;22(11):4305. doi: 10.3390/s22114305.
7
Investigation of the Specification Degradation Mechanism of CMOS Power Amplifier under Thermal Shock Test.CMOS功率放大器在热冲击测试下的规格退化机制研究。
Micromachines (Basel). 2022 May 24;13(6):815. doi: 10.3390/mi13060815.
8
A high duty-cycle, multi-channel, power amplifier for high-resolution radiofrequency encoded magnetic resonance imaging.一种用于高分辨率射频编码磁共振成像的高占空比、多通道、功率放大器。
MAGMA. 2019 Dec;32(6):679-692. doi: 10.1007/s10334-019-00763-1. Epub 2019 Jun 20.
9
An Experimental Investigation of the Degradation of CMOS Low-Noise Amplifier Specifications at Different Temperatures.不同温度下CMOS低噪声放大器性能退化的实验研究
Micromachines (Basel). 2022 Aug 6;13(8):1268. doi: 10.3390/mi13081268.
10
Phase noise in RF and microwave amplifiers.射频和微波放大器中的相位噪声。
IEEE Trans Ultrason Ferroelectr Freq Control. 2012 Dec;59(12):2613-24. doi: 10.1109/TUFFC.2012.2502.

引用本文的文献

1
A Low-Power General Matrix Multiplication Accelerator with Sparse Weight-and-Output Stationary Dataflow.一种采用稀疏权重和输出固定数据流的低功耗通用矩阵乘法加速器。
Micromachines (Basel). 2025 Jan 16;16(1):101. doi: 10.3390/mi16010101.
2
Temperature Characteristics Modeling for GaN PA Based on PSO-ELM.基于粒子群优化极限学习机的氮化镓功率放大器温度特性建模
Micromachines (Basel). 2024 Aug 5;15(8):1008. doi: 10.3390/mi15081008.
3
CS-GA-XGBoost-Based Model for a Radio-Frequency Power Amplifier under Different Temperatures.基于CS-GA-XGBoost的不同温度下射频功率放大器模型

本文引用的文献

1
Wideband Doherty Power Amplifier: A Design Approach.宽带Doherty功率放大器：一种设计方法。
Micromachines (Basel). 2022 Mar 23;13(4):497. doi: 10.3390/mi13040497.
2
A 20-44 GHz Wideband LNA Design Using the SiGe Technology for 5G Millimeter-Wave Applications.一种采用硅锗技术用于5G毫米波应用的20 - 44 GHz宽带低噪声放大器设计。
Micromachines (Basel). 2021 Dec 7;12(12):1520. doi: 10.3390/mi12121520.
3
A GaN HEMT Amplifier Design for Phased Array Radars and 5G New Radios.一种用于相控阵雷达和5G新无线电的氮化镓高电子迁移率晶体管放大器设计。
Micromachines (Basel). 2023 Aug 27;14(9):1673. doi: 10.3390/mi14091673.
4
BPNN-Based Behavioral Modeling of the S-Parameter Variation Characteristics of PAs with Frequency at Different Temperatures.基于反向传播神经网络的功率放大器在不同温度下S参数随频率变化特性的行为建模
Micromachines (Basel). 2022 Oct 26;13(11):1831. doi: 10.3390/mi13111831.
5
Investigation on Temperature Behavior for a GaAs E-pHEMT MMIC LNA.砷化镓增强型高电子迁移率晶体管单片微波集成电路低噪声放大器的温度特性研究
Micromachines (Basel). 2022 Jul 15;13(7):1121. doi: 10.3390/mi13071121.
Micromachines (Basel). 2020 Apr 10;11(4):398. doi: 10.3390/mi11040398.
4
Compact 20-W GaN Internally Matched Power Amplifier for 2.5 GHz to 6 GHz Jammer Systems.用于2.5 GHz至6 GHz干扰系统的紧凑型20瓦氮化镓内部匹配功率放大器。
Micromachines (Basel). 2020 Apr 2;11(4):375. doi: 10.3390/mi11040375.
5
Extreme Learning Machine for Multilayer Perceptron.极限学习机用于多层感知机。
IEEE Trans Neural Netw Learn Syst. 2016 Apr;27(4):809-21. doi: 10.1109/TNNLS.2015.2424995. Epub 2015 May 7.
6
Extreme learning machine for regression and multiclass classification.用于回归和多类分类的极限学习机。
IEEE Trans Syst Man Cybern B Cybern. 2012 Apr;42(2):513-29. doi: 10.1109/TSMCB.2011.2168604. Epub 2011 Oct 6.