Analog IC Placement Generation via Neural Networks from Unlabeled Data

Discover the innovative world of analog integrated circuit design with "Analog IC Placement Generation via Neural Networks from Unlabeled Data" by António Gusmão. Published in 2020 by Springer Nature Switzerland AG, this first edition spans 87 pages and offers a groundbreaking approach to device-level descriptions of input topologies. Gusmão's method focuses on elucidating the relationships between devices within a topology, allowing for a comprehensive understanding of unfamiliar configurations. By leveraging neural networks, this work breaks down complex topologies into manageable components, each subject to the same constraints as those found in training topologies. Ideal for engineers and researchers in the field, this book is a must-have resource for anyone looking to enhance their knowledge of analog IC placement and neural network applications. Dive into this essential read and elevate your expertise in circuit design!