Learning in energy-efficient neuromorphic computing : algorithm and architecture co-design / Nan Zheng, Pinaki Mazumder.
By: Zheng, Nan [author.].
Contributor(s): Mazumder, Pinaki [author.].
Description: pages cm.ISBN: 9781119507383.Subject(s): Neural networks (Computer science)Additional physical formats: Online version:: Learning in energy-efficient neuromorphic computing.DDC classification: 006.3/2 Online resources: Full-text here| Item type | Current location | Call number | Status | Date due | Barcode | Item holds |
|---|---|---|---|---|---|---|
| Book | Skoltech library Shelves | QA76.87 .Z4757 2019 (Browse shelf) | Available | 2000007844 | ||
| E-Book | Skoltech library Shelves | QA76.87 .Z4757 2019 (Browse shelf) | Available |
Includes bibliographical references and index.
Overview -- Fundamentals and learning of artificial neural networks -- Artificial neural networks in hardware -- Operational principles and learning in SNNs -- Hardware implementations of spiking neural networks.
"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"--
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