RF power amplifiers behavioral modeling based on extended neural network with additional dynamic fuzzy weights-Reference-Cited by-同舟云学术

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RF power amplifiers behavioral modeling based on extended neural network with additional dynamic fuzzy weights

Published:2013-08-12 Issue:13 Volume:27 Page:1694-1701
ISSN:0920-5071
Container-title:Journal of Electromagnetic Waves and Applications
language:en
Short-container-title:Journal of Electromagnetic Waves and Applications

Author:

Yuan X.-H.¹,Feng Q.-Y.¹,Zhou L.-C.²

Affiliation:

1. a School of Information Science and Technology, Southwest Jiaotong University , Chengdu , Sichuan , 610031 , China

2. b DTV Engineering & Technology Research Center of Sichuan, Chengdu KTSF Digital Radio & TV Equipment Co. LTD , Chengdu , Sichuan , 610091 , China

Publisher

Informa UK Limited

Subject

Electrical and Electronic Engineering,General Physics and Astronomy,Electronic, Optical and Magnetic Materials

Link

https://www.tandfonline.com/doi/pdf/10.1080/09205071.2013.823121

Reference14 articles.

1. A Highly Efficient Three-Stage Doherty Power Amplifier with Flat Gain for WCDMA Applications

2. AN IMPROVED NONLINEAR CURRENT MODEL FOR GAN HEMT HIGH POWER AMPLIFIER WITH LARGE GATE PERIPHERY

3. X-Band CMOS Power Amplifier Using Mode-Locking Method For Sensor Applications

4. A D-BAND POWER AMPLIFIER WITH 30-GHZ BANDWIDTH AND 4.5-DBM PSAT FOR HIGH-SPEED COMMUNICATION SYSTEM

Cited by 4 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Association of memory terms in a power amplifier modeling functions to the circuit components;Journal of Electromagnetic Waves and Applications;2018-06-25

2. Linearization of traveling-wave tube amplifiers using digitally supported signal injection technique;Journal of Electromagnetic Waves and Applications;2017-09-13

3. An improved large-signal model by artificial neural network for the MOSFETs operating in the breakdown region;Journal of Electromagnetic Waves and Applications;2017-06-19

4. Small-signal modeling for p-n junctions in the breakdown region at different temperatures using artificial neural networks;Journal of Electromagnetic Waves and Applications;2016-08-30

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