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portada Machine Learning Applications in Electronic Design Automation
Type
Physical Book
Illustrated by
Publisher
Author
Language
English
Pages
583
Format
Hardcover
Dimensions
23.4 x 15.6 x 3.3 cm
Weight
1.01 kg.
ISBN13
9783031130731
Categories

Machine Learning Applications in Electronic Design Automation

Haoxing Ren (Illustrated by) · Jiang Hu (Illustrated by) · Springer · Hardcover

Machine Learning Applications in Electronic Design Automation - Ren, Haoxing ; Hu, Jiang

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Synopsis "Machine Learning Applications in Electronic Design Automation "

​This book serves as a single-source reference to key machine learning (ML) applications and methods in digital and analog design and verification. Experts from academia and industry cover a wide range of the latest research on ML applications in electronic design automation (EDA), including analysis and optimization of digital design, analysis and optimization of analog design, as well as functional verification, FPGA and system level designs, design for manufacturing (DFM), and design space exploration. The authors also cover key ML methods such as classical ML, deep learning models such as convolutional neural networks (CNNs), graph neural networks (GNNs), generative adversarial networks (GANs) and optimization methods such as reinforcement learning (RL) and Bayesian optimization (BO). All of these topics are valuable to chip designers and EDA developers and researchers working in digital and analog designs and verification.

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