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Machine Learning Applications in Electronic Design Automation by Haoxing Ren; Jiang Hu is a nonfiction available to read on EtoBox.

What is Machine Learning Applications in Electronic Design Automation about?

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. Serves as a single-source reference to key machine learning (ML) applications and methods in digital and analog design and verification; Covers classical ML methods, as well as deep learning models such as convolutional neural networks (CNNs), graph neural ne

Who reads Machine Learning Applications in Electronic Design Automation?

Author

Haoxing Ren; Jiang Hu

Publisher

Springer International Publishing Springer

Published

2023

Language

EN

ISBN

9783031130748

Category

nonfiction

Subjects

Engineering, Computer Science, Stem