Author : Stutee Pradhan 1
Date of Publication :1st August 2022
Abstract: Topology selection is an important part of analog circuit design and choosing the right topology manually is timeconsuming. We present a new technique of topology selection for CMOS analog circuits. The technique involves predicting different amplifier topologies using a Machine Learning (ML) algorithm. The proposed implementation helps reduce errors and time spent on tedious, repetitive circuit designing tasks. It is aimed at reducing resource requirements and enhancing speed. For demonstration, we have focused on predicting 3 different amplifier topologies namely common drain, cascode amplifier and two stage OPAMP. 9 different performance parameters are used to distinguish different topologies. The topology prediction is performed using 5 Machine Learning algorithms and the performances of the algorithms are compared to find the best algorithm for topology selection.
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