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Open Access Realization of a design-less system for analog integrated circuits

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The 21st century has given rise to a digital world which has significantly impacted on the ways in which humans go about their everyday lives. From being able to speak with whomever you want, whenever you want, wherever you are on your smartphone, to tapping away on your laptop, through to spending hours each day on the internet, the world we live in is firmly digital and it now shapes the way we experience life. When it comes to circuits, analog still has a hugely important role to play. Circuit designer Associate Professor Nobukazu Takai is leading a team of researchers who are applying machine learning to analog circuit design. They are the first team to do this anywhere in the world and, using their method, computers are able to learn how to improve their own circuit specifications.
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Keywords: ANALOG ELECTRONIC DESIGN AUTOMATION; APPLICATION OF Q-LEARNING TO CIRCUIT DESIGN; AUTOMATIC ANALOG INTEGRATED CIRCUIT DESIGN; AUTOMATING ANALOG CIRCUIT DESIGN; OPAMP PARAMETERS; Q-LEARNING

Document Type: Research Article

Publication date: February 1, 2020

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