Design of a neural network-based VCO with high linearity and wide tuning range

Design of a neural network-based VCO with high linearity and wide tuning range

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 ca...

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Bibliographic Details
Main 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
Other Authors: School of Electrical and Electronic Engineering
Format: Article
Language:English
Published: 2019
Subjects:
LC-VCO
Neural Network
DRNTU::Engineering::Electrical and electronic engineering
Online Access:https://hdl.handle.net/10356/106452
http://hdl.handle.net/10220/48929
http://dx.doi.org/10.1109/ACCESS.2019.2915335
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Institution: Nanyang Technological University
Language: English
Description
Summary: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%.

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