SpringerBriefs in Applied Sciences and Technology: Exploring Generative Diffusion Models
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SpringerBriefs in Applied Sciences and Technology: Exploring Generative Diffusion Models
H. M. Eid, Pedro; P. Azevedo, Filipe; C. C. Lourenço, Nuno; M. F. Martins, Ricardo
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.
Details
Published by: Springer
Publication Date: 2025-04-02
Format: Paperback
ISBN-13: 9783031871047
DOI: 10.1007/978-3-031-87105-4
Dimensions: 235cm x155cm
Pages: 78