A machine learning model for predicting frequency of Low Power VCO considering process parameter variations

A low-power CMOS Voltage Controlled Oscillator (VCO) becomes the subject of scrutiny, as LTspice simulations intertwine with machine learning finesse. This paper delves into the analysis of a low-power CMOS Voltage Controlled Oscillator (VCO) through LTspice simulations and machine learning techniqu...

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Published in2023 8th International Conference on Computers and Devices for Communication (CODEC) pp. 1 - 2
Main Authors Sau, Tathagata, Ghosh, Sudipta, Pal, Krishna Kanta, Biswas, Sandan, Sarkhel, Saheli
Format Conference Proceeding
LanguageEnglish
Published IEEE 14.12.2023
Subjects
Focusing
Green products
Linear regression
Machine learning
Semiconductor device modeling
Voltage-controlled oscillators
Wireless communication
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Summary:A low-power CMOS Voltage Controlled Oscillator (VCO) becomes the subject of scrutiny, as LTspice simulations intertwine with machine learning finesse. This paper delves into the analysis of a low-power CMOS Voltage Controlled Oscillator (VCO) through LTspice simulations and machine learning techniques. Focusing on the VCO's behaviour under low-power conditions, a Linear Regression based machine learning model has been automated to accurately predict VCO's output frequency corresponding to process parameter variations of the constituent transistors.
DOI:10.1109/CODEC60112.2023.10465679