Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/106452
Title: Design of a neural network-based VCO with high linearity and wide tuning range
Authors: Guo, Rui
Qian, Kun
Wei, Jinping
Chen, Tupei
Liu, Yanchen
Kong, Deyu
Wang, J. J.
Wu, Yuancong
Hu, S. G.
Yu, Qi
Liu, Yang
Keywords: LC-VCO
Neural Network
DRNTU::Engineering::Electrical and electronic engineering
Issue Date: 2019
Source: Guo, R., Qian, K., Wei, J., Chen, T., Liu, Y., Kong, D., . . . Liu, Y. (2019). Design of a neural network-based VCO with high linearity and wide tuning range. IEEE Access, 7, 60120-60125. doi:10.1109/ACCESS.2019.2915335
Series/Report no.: IEEE Access
Abstract: In this paper, a 2 GHz LC-VCO with neural network (Multilayer Perceptron) has been designed in a 0.13 ţm CMOS technology. With the integrated neural network, the linearity and tuning range of the LC-VCO has been substantially improved. Compared to a conventional VCO design, the proposed technique can improve the linearity by selecting optimized bias voltages obtained from the output of the neuron network. The result shows that the tuning nonlinearity of the proposed VCO is further optimized from 0.335% to 0.254%.
URI: https://hdl.handle.net/10356/106452
http://hdl.handle.net/10220/48929
DOI: 10.1109/ACCESS.2019.2915335
Schools: School of Electrical and Electronic Engineering 
Rights: © 2019 IEEE. Translations and content mining are permitted for academic research only. Personal use is also permitted, but republication/redistribution requires IEEE permission. See http://www.ieee.org/publications_standards/publications/rights/index.html for more information.
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:EEE Journal Articles

Files in This Item:
File Description SizeFormat 
Design of a neural network-based VCO with high linearity and wide tuning range.pdf6.97 MBAdobe PDFThumbnail
View/Open

SCOPUSTM   
Citations 50

6
Updated on Dec 1, 2023

Web of ScienceTM
Citations 50

5
Updated on Oct 30, 2023

Page view(s) 50

508
Updated on Dec 8, 2023

Download(s) 50

135
Updated on Dec 8, 2023

Google ScholarTM

Check

Altmetric


Plumx

Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.