Efficient Analog Integrated Circuit Sizing with GenAI
Exploring Generative Diffusion Models
Springer Nature Switzerland
ISBN 978-3-031-87105-4
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eBook. PDF
2025
XVII, 78 p. 38 illus., 28 illus. in color..
In englischer Sprache
Umfang: 78 S.
Verlag: Springer Nature Switzerland
ISBN: 978-3-031-87105-4
Weiterführende bibliografische Daten
Das Werk ist Teil der Reihe: SpringerBriefs in Applied Sciences and Technology SpringerBriefs in Computational Intelligence
Produktbeschreibung
This book focuses on the automation of analog integrated circuit design, particularly the sizing process. It introduces an innovative approach leveraging generative artificial intelligence, specifically denoising diffusion probabilistic models (DDPM). The proposed methodology provides a robust solution for generating circuit designs that meet specific performance constraints, offering a significant improvement over conventional techniques. By integrating advanced machine learning models into the design workflow, the book showcases a transformative way to streamline the process while maintaining accuracy and reliability.
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