Learning in energy-efficient neuromorphic computing: algorithm and architecture co-design

"This book focuses on how to build energy-efficient hardware for neural network with learning capabilities. One of the striking features of this book is that it strives to provide a co-design and co-optimization methodologies for building hardware neural networks that can learn. The book provid...

Ausführliche Beschreibung

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Bibliographische Detailangaben
1. Verfasser: Zheng, Nan (VerfasserIn)
Format: Elektronisch E-Book
Sprache:English
Veröffentlicht: Hoboken, New Jersey Wiley-IEEE Press [2019]
Schlagworte:
Online-Zugang:FHI01
Volltext
Zusammenfassung:"This book focuses on how to build energy-efficient hardware for neural network with learning capabilities. One of the striking features of this book is that it strives to provide a co-design and co-optimization methodologies for building hardware neural networks that can learn. The book provides a complete picture from high-level algorithm to low-level implementation details. The book also covers many fundamentals and essentials in neural networks, e.g., deep learning, as well as hardware implementation of neural networks. This book will serve as a good resource for teaching and training undergraduate and graduate students about the latest generation neural networks with powerful learning capabilities"--
Beschreibung:Print version record
Beschreibung:1 Online-Resource (296 pages)
ISBN:9781119507369
9781119507390
9781119507406

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