Automated Design Optimization for CMOS Rectifier Using Deep Neural Network (DNN)

A previously designed CMOS rectifier is optimized with the help of Deep Neural Network (DNN) to identify maximum power conversion efficiency (PCE) for various input RF power (from antenna) and load conditions. The condition for an additional improvement of 1.8% in PCE is identified and cross validat...

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Bibliographic Details
Published in2019 IEEE Wireless Power Transfer Conference (WPTC) pp. 599 - 603
Main Authors Ho, Heng Wah, Lau, Wendy W.Y.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.06.2019
Subjects
CMOS Rectifier
Deep Learning
Deep Neural Network
Neuron
Optimization
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Summary:A previously designed CMOS rectifier is optimized with the help of Deep Neural Network (DNN) to identify maximum power conversion efficiency (PCE) for various input RF power (from antenna) and load conditions. The condition for an additional improvement of 1.8% in PCE is identified and cross validated with simulation result.
ISSN:2573-7651
DOI:10.1109/WPTC45513.2019.9055537